Forwarded from Apply Time
- 1. A cover letter
- 2. Full CV and list of publications
- 3. Two reference letters.
If you have any questions, do not hesitate to contact Prof. Ioannis Pitas and Prof. Chongsheng Zhang via Email.
✔️ @ApplyTime
- 2. Full CV and list of publications
- 3. Two reference letters.
If you have any questions, do not hesitate to contact Prof. Ioannis Pitas and Prof. Chongsheng Zhang via Email.
✔️ @ApplyTime
Forwarded from Apply Time
MSc and PhD Studentships
The Department of Social Statistics and Demography(SSD) at the University of Southampton is looking for graduates interested in studying for MSc and/or PhD in social statistics, demography, quantitative social science and global health. They invite you to learn more about their MSc taught courses in Demography, Global Health, Social Research Methods with Applied Statistics, Applied Statistics and Data Analytics for Government, and their Social Statistics and Demography PhD programme.
Postgraduate funding opportunities
They understand that securing funding for postgraduate education and training is increasingly competitive. Their department wants to provide support to candidates who share their disciplinary interests in preparing funding applications. They highlight some upcoming UK and international scholarship opportunities and encourage you to contact them about these schemes or to discuss other possible funding sources.
The South Coast Doctoral Training Partnership (SCDTP) MSc/PhD and PhD scholarships
The SCDTP will be awarding a minimum of 38 studentships per year to social scientists carrying out PhD studies or Masters + PhD studies at the University of Southampton or one of the other two partner institutions. They are pleased to highlight the steer of some of these awards towards advanced training in Advanced Quantitative Methods (AQM), Data Sets/Skills, and interdisciplinary research. The deadline for Academic Year 2022/23 applications is midnight 24th January 2022.
For more information about these scholarship opportunities, please visit the SCDTP website https://southcoastdtp.ac.uk/To enquire about how SSD might be able to support your application, please email the SSD Director of Postgraduate Research -Professor Vicky Hosegood [email protected] contact a member of their academic staff whose research interests align with yours.
Wellcome Trust and Commonwealth scholarships for the MSc Global Health
Their department will be awarding three WellcomeTrust MSc scholarships for students starting the MSc Global Health in 2022/23 (two of which are specifically for students from low-and middle-income countries). There is also an opportunity for students wishing to take this programme to apply for a Commonwealth Shared Scholarship. To find out more about the MSc Global Health please visit their website www.soton.ac.uk/globalhealthand the MSc Global Health programme director –Dr Sarah Neal [email protected]
Commonwealth Shared Scholarship for the MSc in Demographyor MSc in Global Health or MSc in Gerontology
One Commonwealth Shared Scholarship will be available for study on one of three programmes in the Faculty of Social Sciences-MSc in Demography, MSc in Global Health or MSc in Gerontology. More information about theCommonwealth Scheme and application process are available here. The deadline for the applications is at 4pm 20th December 2021. They are happy to speak to people interested in applying for the Commonwealth scholarship or finding out more about the taught courses that They offer with the Social Statistics and Demography department. Please contact the MSc Demography programme director –Dr Olga Maslovskaya [email protected]
✔️ @ApplyTime
The Department of Social Statistics and Demography(SSD) at the University of Southampton is looking for graduates interested in studying for MSc and/or PhD in social statistics, demography, quantitative social science and global health. They invite you to learn more about their MSc taught courses in Demography, Global Health, Social Research Methods with Applied Statistics, Applied Statistics and Data Analytics for Government, and their Social Statistics and Demography PhD programme.
Postgraduate funding opportunities
They understand that securing funding for postgraduate education and training is increasingly competitive. Their department wants to provide support to candidates who share their disciplinary interests in preparing funding applications. They highlight some upcoming UK and international scholarship opportunities and encourage you to contact them about these schemes or to discuss other possible funding sources.
The South Coast Doctoral Training Partnership (SCDTP) MSc/PhD and PhD scholarships
The SCDTP will be awarding a minimum of 38 studentships per year to social scientists carrying out PhD studies or Masters + PhD studies at the University of Southampton or one of the other two partner institutions. They are pleased to highlight the steer of some of these awards towards advanced training in Advanced Quantitative Methods (AQM), Data Sets/Skills, and interdisciplinary research. The deadline for Academic Year 2022/23 applications is midnight 24th January 2022.
For more information about these scholarship opportunities, please visit the SCDTP website https://southcoastdtp.ac.uk/To enquire about how SSD might be able to support your application, please email the SSD Director of Postgraduate Research -Professor Vicky Hosegood [email protected] contact a member of their academic staff whose research interests align with yours.
Wellcome Trust and Commonwealth scholarships for the MSc Global Health
Their department will be awarding three WellcomeTrust MSc scholarships for students starting the MSc Global Health in 2022/23 (two of which are specifically for students from low-and middle-income countries). There is also an opportunity for students wishing to take this programme to apply for a Commonwealth Shared Scholarship. To find out more about the MSc Global Health please visit their website www.soton.ac.uk/globalhealthand the MSc Global Health programme director –Dr Sarah Neal [email protected]
Commonwealth Shared Scholarship for the MSc in Demographyor MSc in Global Health or MSc in Gerontology
One Commonwealth Shared Scholarship will be available for study on one of three programmes in the Faculty of Social Sciences-MSc in Demography, MSc in Global Health or MSc in Gerontology. More information about theCommonwealth Scheme and application process are available here. The deadline for the applications is at 4pm 20th December 2021. They are happy to speak to people interested in applying for the Commonwealth scholarship or finding out more about the taught courses that They offer with the Social Statistics and Demography department. Please contact the MSc Demography programme director –Dr Olga Maslovskaya [email protected]
✔️ @ApplyTime
Forwarded from Apply Time
A Postdoc position is open at University of Strasbourg (ICube lab) - France
Deep Learning, Domain Adaptation, Multi-Modal Representations
The position will be funded for two years (initially for one year, renewable for an additional year). The candidate will join the SDC research team under the supervision of Dr Thomas Lampert, the Chair of Data Science and Artificial Intelligence, and join his international team of PhD students and engineer to develop novel deep learning approaches to domain invariant representation learning (particularly in multi-modal data), with application (but not restricted) to Medical Imaging and Remote Sensing. The funding is not connected to a particular project, so it is the perfect opportunity for a strong candidate to explore new directions under the supervision of the Chair.
The successful candidate will have (or will soon obtain) a PhD in computer science or related domain and have experience in deep learning and applied machine learning and a strong level of written and spoken English. Experience with transformers, GANs, autoencoders, and/or unsupervised/self-supervised DL (autoencoders, etc) would be a plus. You will join a growing team and will have the freedom to follow your interests in a direction complementary to the abovementioned research focusses. You will be expected to target leading outlets in the field of machine learning and a strong track record in CVPR/ICCV/ECCV, NIPS/ICML/ICLR, or PAMI/IJCV/TIP. Candidates who are able to carry out the highest quality research independently, to co-supervise PhD students, and to give their input on a number of projects being carried out in the team are pursued. You will have access to state-of-the-art hardware for deep learning.
Send a letter of motivation, your CV, and an example publication to Thomas Lamper and Gisèle Burgart ([email protected] and [email protected] - !remove the numbers!) with the subject beginning with [Chaire Postdoc].
The position will remain open until a suitable candidate is found and the starting date will be agreed upon with the successful candidate (but can start ASAP).
Detailed Description: https://seafile.unistra.fr/f/5931f91dcffb401db566/?dl=1
✔️ @ApplyTime
Deep Learning, Domain Adaptation, Multi-Modal Representations
The position will be funded for two years (initially for one year, renewable for an additional year). The candidate will join the SDC research team under the supervision of Dr Thomas Lampert, the Chair of Data Science and Artificial Intelligence, and join his international team of PhD students and engineer to develop novel deep learning approaches to domain invariant representation learning (particularly in multi-modal data), with application (but not restricted) to Medical Imaging and Remote Sensing. The funding is not connected to a particular project, so it is the perfect opportunity for a strong candidate to explore new directions under the supervision of the Chair.
The successful candidate will have (or will soon obtain) a PhD in computer science or related domain and have experience in deep learning and applied machine learning and a strong level of written and spoken English. Experience with transformers, GANs, autoencoders, and/or unsupervised/self-supervised DL (autoencoders, etc) would be a plus. You will join a growing team and will have the freedom to follow your interests in a direction complementary to the abovementioned research focusses. You will be expected to target leading outlets in the field of machine learning and a strong track record in CVPR/ICCV/ECCV, NIPS/ICML/ICLR, or PAMI/IJCV/TIP. Candidates who are able to carry out the highest quality research independently, to co-supervise PhD students, and to give their input on a number of projects being carried out in the team are pursued. You will have access to state-of-the-art hardware for deep learning.
Send a letter of motivation, your CV, and an example publication to Thomas Lamper and Gisèle Burgart ([email protected] and [email protected] - !remove the numbers!) with the subject beginning with [Chaire Postdoc].
The position will remain open until a suitable candidate is found and the starting date will be agreed upon with the successful candidate (but can start ASAP).
Detailed Description: https://seafile.unistra.fr/f/5931f91dcffb401db566/?dl=1
✔️ @ApplyTime
Forwarded from Apply Time
Openings in Université Côte d'Azur (Inria/CNRS I3S) on multimedia processing, immersive systems, and ML
We are currently seeking motivated candidates for multiple job openings in the Inria and CNRS I3S laboratories of Université Côte d'Azur on various topics in multimedia analysis and processing, immersive systems, and user motion modeling. Please consult the following links for detailed post descriptions and application information:
== Engineer positions ==
- Engineer in computer vision and data processing (https://recrutement.inria.fr/public/classic/en/offres/2021-04120)
- Engineer in immersive multimedia systems (https://www.i3s.univ-cotedazur.fr/~sassatelli/files/Engineer_position_UCA_AI4Media.pdf)
== PhD position ==
- PhD thesis in multimedia analysis (https://www.i3s.univ-cotedazur.fr/~sassatelli/files/PhDposition_IRIT-I3S_ANR_TRACTIVE.pdf)
== Master's internships ==
- Modeling 6 DoF human motion data in extended reality (https://www-sop.inria.fr/members/Hui-Yin.Wu/offers/stage_creattive3d_6dof_modeling.pdf)
- Image and text processing for multimodal film analysis (https://www-sop.inria.fr/members/Hui-Yin.Wu/offers/stage_tractive_data.pdf)
Best Regards,
Hui-Yin Wu
--
Hui-Yin Wu (Helen)
Research scientist - Inria Starting Faculty Position
Biovision Team @ Centre Inria d'Université Côte d'Azur
✔️ @ApplyTime
We are currently seeking motivated candidates for multiple job openings in the Inria and CNRS I3S laboratories of Université Côte d'Azur on various topics in multimedia analysis and processing, immersive systems, and user motion modeling. Please consult the following links for detailed post descriptions and application information:
== Engineer positions ==
- Engineer in computer vision and data processing (https://recrutement.inria.fr/public/classic/en/offres/2021-04120)
- Engineer in immersive multimedia systems (https://www.i3s.univ-cotedazur.fr/~sassatelli/files/Engineer_position_UCA_AI4Media.pdf)
== PhD position ==
- PhD thesis in multimedia analysis (https://www.i3s.univ-cotedazur.fr/~sassatelli/files/PhDposition_IRIT-I3S_ANR_TRACTIVE.pdf)
== Master's internships ==
- Modeling 6 DoF human motion data in extended reality (https://www-sop.inria.fr/members/Hui-Yin.Wu/offers/stage_creattive3d_6dof_modeling.pdf)
- Image and text processing for multimodal film analysis (https://www-sop.inria.fr/members/Hui-Yin.Wu/offers/stage_tractive_data.pdf)
Best Regards,
Hui-Yin Wu
--
Hui-Yin Wu (Helen)
Research scientist - Inria Starting Faculty Position
Biovision Team @ Centre Inria d'Université Côte d'Azur
✔️ @ApplyTime
Inria
Ingénieur·e en traitement de données et vision par ordinateur
Offre d'emploi Inria
Forwarded from Apply Time
UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM), Queen Mary University of London
https://www.aim.qmul.ac.uk/
12+ fully-funded PhD studentships to start September 2022
Covers fees and a stipend for four years
Application deadline: 30 January 2022
Why apply to the AIM Programme?
4-year fully-funded PhD studentships available
Extensive choice of projects, drawing on a supervisory team of over 30 academics
Access to cutting-edge facilities and expertise in artificial intelligence (AI) and music/audio technology
Comprehensive technical training at the intersection of AI and music through a personalized programme
Partnerships with over 25 companies and cultural institutions in the music, audio and creative sectors
More information on the AIM Programme can be found at: https://www.aim.qmul.ac.uk/
Programme structure
Our Centre for Doctoral Training (CDT) offers a four year training programme where students will carry out a research project in the intersection of AI and music, supported by taught specialist modules, industrial placements, and skills training. Find out more about the programme structure at: https://www.aim.qmul.ac.uk/about/
Who can apply?
We are on the lookout for outstanding students interested in the intersection of music/audio technology and AI. Successful applicants will have the following profile:
Hold or be completing a Masters degree at distinction or first class level, or equivalent, in Computer Science, Electronic Engineering, Music/Audio Technology, Physics, Mathematics, Music or Psychology. In exceptional circumstances we accept applicants with a first class Bachelors degree who do not hold a Masters degree, provided that applicants can provide evidence of equivalent research experience, industry experience, or specialist training.
Programming skills are strongly desirable; however we do not consider this to be an essential criterion if candidates have complementary strengths.
Musical training (any of performance, production, composition or theory) is desirable but not a prerequisite.
For this call we are inviting applications from UK Home students and International students, as well as students supported by national and international funding bodies, such as the China Scholarship Council (CSC), CONACYT, and the Commonwealth PhD Scholarship scheme. Queen Mary’s commitment to our diverse and inclusive community is embedded in our student admissions processes. We particularly welcome applications from women and under-represented groups, and from applicants in all stages of life.
Funding
For this call we offer 12+ fully-funded 4-year PhD studentships available for students starting in September 2022 which will cover the cost of tuition fees and will provide an annual tax-free stipend (£17,609 in 2021/22). The CDT will also provide funding for conference travel, equipment, and for attending other CDT-related events.
The AIM programme also welcomes applications from students who have sponsorship for PhD study from numerous international funding agencies and also accepts self-funded students. For more information on external PhD studentships and self-funded students please visit https://www.aim.qmul.ac.uk/apply .
Apply Now
Information on applications and PhD topics can be found at: https://www.aim.qmul.ac.uk/apply
Application deadline: 30 January 2022
For further information on eligibility, funding and the application process please visit our website. Please email any questions to [email protected]
--
Dr Emmanouil Benetos
Senior Lecturer | Queen Mary University of London
Turing Fellow | The Alan Turing Institute
T + 44 (0) 20 7882 6206
[email protected]
https://www.eecs.qmul.ac.uk/~emmanouilb/
✔️ @ApplyTime
https://www.aim.qmul.ac.uk/
12+ fully-funded PhD studentships to start September 2022
Covers fees and a stipend for four years
Application deadline: 30 January 2022
Why apply to the AIM Programme?
4-year fully-funded PhD studentships available
Extensive choice of projects, drawing on a supervisory team of over 30 academics
Access to cutting-edge facilities and expertise in artificial intelligence (AI) and music/audio technology
Comprehensive technical training at the intersection of AI and music through a personalized programme
Partnerships with over 25 companies and cultural institutions in the music, audio and creative sectors
More information on the AIM Programme can be found at: https://www.aim.qmul.ac.uk/
Programme structure
Our Centre for Doctoral Training (CDT) offers a four year training programme where students will carry out a research project in the intersection of AI and music, supported by taught specialist modules, industrial placements, and skills training. Find out more about the programme structure at: https://www.aim.qmul.ac.uk/about/
Who can apply?
We are on the lookout for outstanding students interested in the intersection of music/audio technology and AI. Successful applicants will have the following profile:
Hold or be completing a Masters degree at distinction or first class level, or equivalent, in Computer Science, Electronic Engineering, Music/Audio Technology, Physics, Mathematics, Music or Psychology. In exceptional circumstances we accept applicants with a first class Bachelors degree who do not hold a Masters degree, provided that applicants can provide evidence of equivalent research experience, industry experience, or specialist training.
Programming skills are strongly desirable; however we do not consider this to be an essential criterion if candidates have complementary strengths.
Musical training (any of performance, production, composition or theory) is desirable but not a prerequisite.
For this call we are inviting applications from UK Home students and International students, as well as students supported by national and international funding bodies, such as the China Scholarship Council (CSC), CONACYT, and the Commonwealth PhD Scholarship scheme. Queen Mary’s commitment to our diverse and inclusive community is embedded in our student admissions processes. We particularly welcome applications from women and under-represented groups, and from applicants in all stages of life.
Funding
For this call we offer 12+ fully-funded 4-year PhD studentships available for students starting in September 2022 which will cover the cost of tuition fees and will provide an annual tax-free stipend (£17,609 in 2021/22). The CDT will also provide funding for conference travel, equipment, and for attending other CDT-related events.
The AIM programme also welcomes applications from students who have sponsorship for PhD study from numerous international funding agencies and also accepts self-funded students. For more information on external PhD studentships and self-funded students please visit https://www.aim.qmul.ac.uk/apply .
Apply Now
Information on applications and PhD topics can be found at: https://www.aim.qmul.ac.uk/apply
Application deadline: 30 January 2022
For further information on eligibility, funding and the application process please visit our website. Please email any questions to [email protected]
--
Dr Emmanouil Benetos
Senior Lecturer | Queen Mary University of London
Turing Fellow | The Alan Turing Institute
T + 44 (0) 20 7882 6206
[email protected]
https://www.eecs.qmul.ac.uk/~emmanouilb/
✔️ @ApplyTime
Postdoc position in A*STAR Singapore, computer vision for privacy and memorability in egocentric images
Career - Agency for Science, Technology and Research (a-star.edu.sg)
Scientist, Social and Cognitive Computing, IHPC
Posting Date : 02 Sep 2021 | Closing Date :01 Sep 2022
JOB DESCRIPTION
The Social and Cognitive Computing (SCC) department of the Institute of High-Performance Computing (IHPC) is seeking an exceptional research scientist to expand our dynamic and multidisciplinary team. Our current team members have degrees in computer science, information systems, psychology, cognitive science and neuroscience from Berkeley, CMU, EFPL, KU Leuven, NTU, NUS, MIT, Stanford, SUTD, UIUC, etc. We work on some of the most crucial, incredibly hard, and future-oriented problems in AI, that lie at the cross-disciplinary convergence of cognitive science, psychology, behavioural sciences, artificial intelligence, computational modelling & simulation.
For this position, the successful candidate will be expected to:
· Develop image/video processing algorithms for detection and tracking of artefacts relevant to privacy and memorability in images - Eg. human face, objects, handwriting etc.
· Develop and evaluate several obfuscation strategies such as blurring, masking etc. and evaluate their effectiveness.
· Develop and evaluate methods for estimation of memorability of images using multimodal data (image, gaze, brain-image etc.). Design and conduct user-studies to gather data from people using wearable cameras. Conduct surveys regarding users' privacy preferences, memorability of images and analyse factors underlying memorability and privacy sensitivity.
· Build attention based, incremental and autonomous machine learning models that use a data stream of images to estimate memorability and sensitivity of images.
· Develop privacy aware systems (Eg. serious games) that can be used for memory augmentation and training.
· Develop prototypes to demonstrate the effectiveness and efficiency of algorithms in collaboration with research team members.
· Provide timely, accurate and detailed reports and presentations and demonstrations.
JOB REQUIREMENT
· PhD in Computer Science, Computer Engineering, Electrical Engineering or related fields
· Research experience in at least in one of the following areas: computer vision, signal processing, brain imaging, gaze analysis, pattern recognition, object detection, image analysis and deep learning. Track record of publication in highly rated journals and conferences in AI, computational neuroscience.
· Knowledge/experience in computational methods and technology used for dealing with memory augmentation, neuro-psychiatric conditions, cognitive disorders.
· Proficiency in neural networks, image processing, statistics.
· Experience in image memorability, incremental learning, autoML will be an advantage.
· Excellent programming skills in languages such as Python, R , Java, C++.
· Good problem solving skills, team player, good interpersonal, presentation and communication skills
· Awareness of good scientific practices
· Motivated and resourceful individual
✔️ @ApplyTime
Career - Agency for Science, Technology and Research (a-star.edu.sg)
Scientist, Social and Cognitive Computing, IHPC
Posting Date : 02 Sep 2021 | Closing Date :01 Sep 2022
JOB DESCRIPTION
The Social and Cognitive Computing (SCC) department of the Institute of High-Performance Computing (IHPC) is seeking an exceptional research scientist to expand our dynamic and multidisciplinary team. Our current team members have degrees in computer science, information systems, psychology, cognitive science and neuroscience from Berkeley, CMU, EFPL, KU Leuven, NTU, NUS, MIT, Stanford, SUTD, UIUC, etc. We work on some of the most crucial, incredibly hard, and future-oriented problems in AI, that lie at the cross-disciplinary convergence of cognitive science, psychology, behavioural sciences, artificial intelligence, computational modelling & simulation.
For this position, the successful candidate will be expected to:
· Develop image/video processing algorithms for detection and tracking of artefacts relevant to privacy and memorability in images - Eg. human face, objects, handwriting etc.
· Develop and evaluate several obfuscation strategies such as blurring, masking etc. and evaluate their effectiveness.
· Develop and evaluate methods for estimation of memorability of images using multimodal data (image, gaze, brain-image etc.). Design and conduct user-studies to gather data from people using wearable cameras. Conduct surveys regarding users' privacy preferences, memorability of images and analyse factors underlying memorability and privacy sensitivity.
· Build attention based, incremental and autonomous machine learning models that use a data stream of images to estimate memorability and sensitivity of images.
· Develop privacy aware systems (Eg. serious games) that can be used for memory augmentation and training.
· Develop prototypes to demonstrate the effectiveness and efficiency of algorithms in collaboration with research team members.
· Provide timely, accurate and detailed reports and presentations and demonstrations.
JOB REQUIREMENT
· PhD in Computer Science, Computer Engineering, Electrical Engineering or related fields
· Research experience in at least in one of the following areas: computer vision, signal processing, brain imaging, gaze analysis, pattern recognition, object detection, image analysis and deep learning. Track record of publication in highly rated journals and conferences in AI, computational neuroscience.
· Knowledge/experience in computational methods and technology used for dealing with memory augmentation, neuro-psychiatric conditions, cognitive disorders.
· Proficiency in neural networks, image processing, statistics.
· Experience in image memorability, incremental learning, autoML will be an advantage.
· Excellent programming skills in languages such as Python, R , Java, C++.
· Good problem solving skills, team player, good interpersonal, presentation and communication skills
· Awareness of good scientific practices
· Motivated and resourceful individual
✔️ @ApplyTime
Ph.D. Position: Machi
The Applied Media Systems group of Ilmenau University of Technology in Ilmenau, Germany, is looking for candidates for a half-time Ph.D position (20 hours/week), in the area of machine learning for audio. The duties include teaching seminars and supervising students in Media Technology and Electrical Engineering.
Duration: starting with 3 years, can be extended up to 6 years.
Starting date: February 1st, 2022.
Our group works on audio coding, filter banks, autoencoders, stochastic optimization, audio and musical source separation.
The ideal candidate will have solid knowledge in digital signal processing and machine learning for audio and video.
Requirement: Master in Electrical Engineering or similar, with focus on digital signal processing and/or machine learning for audio and/or video.
Essential is curiosity for learning, ideas and ingenuity.
If you are interested, send me an email, with a few of your main achievements:
[email protected]
The official applications link is:
https://jobundkarriere.tu-ilmenau.de/jobposting/f8e166014bb5382777de6fee7cb10d877f98a70b0
Our groups website is:
https://www.tu-ilmenau.de/mt-ams
Many greetings,
Gerald Schuller
ne Learning in Audio, TU Ilmenau, Germany
✔️ @ApplyTime
The Applied Media Systems group of Ilmenau University of Technology in Ilmenau, Germany, is looking for candidates for a half-time Ph.D position (20 hours/week), in the area of machine learning for audio. The duties include teaching seminars and supervising students in Media Technology and Electrical Engineering.
Duration: starting with 3 years, can be extended up to 6 years.
Starting date: February 1st, 2022.
Our group works on audio coding, filter banks, autoencoders, stochastic optimization, audio and musical source separation.
The ideal candidate will have solid knowledge in digital signal processing and machine learning for audio and video.
Requirement: Master in Electrical Engineering or similar, with focus on digital signal processing and/or machine learning for audio and/or video.
Essential is curiosity for learning, ideas and ingenuity.
If you are interested, send me an email, with a few of your main achievements:
[email protected]
The official applications link is:
https://jobundkarriere.tu-ilmenau.de/jobposting/f8e166014bb5382777de6fee7cb10d877f98a70b0
Our groups website is:
https://www.tu-ilmenau.de/mt-ams
Many greetings,
Gerald Schuller
ne Learning in Audio, TU Ilmenau, Germany
✔️ @ApplyTime
Post-doc/research engineer position in deep learning for sentiment analysis
The Machine Learning team of the LITIS laboratory is still looking for a post-doctoral researcher or a research engineer, for a position in deep learning for sentiment analysis, funded by by the ANR CATCH project.
Title: Deep Learning for opinion mining in human testimonials related to industrial accident
Keywords: deep learning, NLP, sentiment analysis, twitter
Location: LITIS lab., University or Rouen Normandy, Rouen, France
Duration: 18-months, starting as soon as possible
Salary: ~2300€/month (before income tax), including social security coverage in line with French regulations
Please find the detailed description of the position attached to this email.
This position is still unfilled, so please feel free to forward to anyone who might be interested.
Best regards,
--
Simon Bernard
LITIS / NormaSTIC FR CNRS 3638
Université de Rouen Normandie, France
https://pagesperso.litislab.fr/sbernard/
✔️ @ApplyTime
The Machine Learning team of the LITIS laboratory is still looking for a post-doctoral researcher or a research engineer, for a position in deep learning for sentiment analysis, funded by by the ANR CATCH project.
Title: Deep Learning for opinion mining in human testimonials related to industrial accident
Keywords: deep learning, NLP, sentiment analysis, twitter
Location: LITIS lab., University or Rouen Normandy, Rouen, France
Duration: 18-months, starting as soon as possible
Salary: ~2300€/month (before income tax), including social security coverage in line with French regulations
Please find the detailed description of the position attached to this email.
This position is still unfilled, so please feel free to forward to anyone who might be interested.
Best regards,
--
Simon Bernard
LITIS / NormaSTIC FR CNRS 3638
Université de Rouen Normandie, France
https://pagesperso.litislab.fr/sbernard/
✔️ @ApplyTime
Simon Bernard
- Simon Bernard
Simon Bernard, PhD, assistant professor at the University of Rouen Normandie (France) and member of the 'Machine Learning' research team at the LITIS lab.
Open Post-Doc position in Artificial Intelligence and Image Analysis for Extraction of graphic elements in comics books for emotion recognitionPost-doctoral research position - L3i - La Rochelle France
---------------------------------------------------------------------------------------------------------------------------
Title : Extraction of graphic elements in comics books for emotion recognition
The L3i laboratory has one open post-doc position in computer science, in the specific field of document image analysis and pattern recognition
Duration: 12 months (an extension of 12 months will be possible)
Position available from: As soon as possible, 2021
Salary: approximately 2100 € / month (net)
Place: L3i lab, University of La Rochelle, France
Specialty: Computer Science/ Image Processing/ Document Analysis/ Pattern Recognition
Contact: Jean-Christophe BURIE (jcburie [at] univ-lr.fr)
Position Description
The L3i is a research lab of the University of La Rochelle. La Rochelle is a city in the south west of France on the Atlantic coast and is one of the most attractive and dynamic cities in France. The L3i works since several years on document analysis and has developed a well-known expertise in ‘Bande dessinée”, manga and comics analysis, indexing and understanding.
The work done by the post-doc will take part in the context of SAiL (Sequential Art Image Laboratory) a joint laboratory involving L3i and a private company. The objective is to create innovative tools to index and interact with digitised comics. The work will be done in a team of 10 researchers and engineers.
The work will consist in developing original approaches for extracting and recognizing graphics elements in comic panels in order to recognize emotions. Authors usually used different strategies for representing emotions such as shape of speech balloon, specific symbols, colour of the faces, etc. These elements are drawn among the other graphic elements (main characters, scenery, …) making the localisation and the extraction challenging. In order to extract these specific elements, the development of original approaches will be necessary. Deep learning-based strategies can be explored to reach this goal. This work will be done in collaboration with other researchers working on text understanding.
Qualifications
Candidates must have a completed PhD and a research experience in image processing and analysis, pattern recognition. Some knowledge and experience in deep learning are also recommended.
General Qualifications
• Good programming skills mastering at least one programming language like Python, Java, C/C++
• Good teamwork skills
• Good writing skills and proficiency in written and spoken English or French
Applications
Candidates should send a CV and a motivation letter to jcburie[at]univ-lr.fr.
--
Jean-Christophe Burie
--
Vice-président campus numérique système d'information
Professeur des Universités
Département Informatique - Laboratoire L3i
- Directeur Adjoint du Laboratoire Informatique Image Interaction (L3i)
- Directeur du laboratoire Commun SAIL (Sequential Art Image Laboratory)
(+33) 06 42 05 36 26 / (+33) 05 46 45 87 62
[email protected]
Laboratoire Informatique, Image et Interaction (L3i)
La Rochelle Université
Avenue Michel Crépeau
17042 La Rochelle cedex 1
l3i.univ-larochelle.fr
univ-larochelle.fr
✔️ @ApplyTime
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Title : Extraction of graphic elements in comics books for emotion recognition
The L3i laboratory has one open post-doc position in computer science, in the specific field of document image analysis and pattern recognition
Duration: 12 months (an extension of 12 months will be possible)
Position available from: As soon as possible, 2021
Salary: approximately 2100 € / month (net)
Place: L3i lab, University of La Rochelle, France
Specialty: Computer Science/ Image Processing/ Document Analysis/ Pattern Recognition
Contact: Jean-Christophe BURIE (jcburie [at] univ-lr.fr)
Position Description
The L3i is a research lab of the University of La Rochelle. La Rochelle is a city in the south west of France on the Atlantic coast and is one of the most attractive and dynamic cities in France. The L3i works since several years on document analysis and has developed a well-known expertise in ‘Bande dessinée”, manga and comics analysis, indexing and understanding.
The work done by the post-doc will take part in the context of SAiL (Sequential Art Image Laboratory) a joint laboratory involving L3i and a private company. The objective is to create innovative tools to index and interact with digitised comics. The work will be done in a team of 10 researchers and engineers.
The work will consist in developing original approaches for extracting and recognizing graphics elements in comic panels in order to recognize emotions. Authors usually used different strategies for representing emotions such as shape of speech balloon, specific symbols, colour of the faces, etc. These elements are drawn among the other graphic elements (main characters, scenery, …) making the localisation and the extraction challenging. In order to extract these specific elements, the development of original approaches will be necessary. Deep learning-based strategies can be explored to reach this goal. This work will be done in collaboration with other researchers working on text understanding.
Qualifications
Candidates must have a completed PhD and a research experience in image processing and analysis, pattern recognition. Some knowledge and experience in deep learning are also recommended.
General Qualifications
• Good programming skills mastering at least one programming language like Python, Java, C/C++
• Good teamwork skills
• Good writing skills and proficiency in written and spoken English or French
Applications
Candidates should send a CV and a motivation letter to jcburie[at]univ-lr.fr.
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Jean-Christophe Burie
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Vice-président campus numérique système d'information
Professeur des Universités
Département Informatique - Laboratoire L3i
- Directeur Adjoint du Laboratoire Informatique Image Interaction (L3i)
- Directeur du laboratoire Commun SAIL (Sequential Art Image Laboratory)
(+33) 06 42 05 36 26 / (+33) 05 46 45 87 62
[email protected]
Laboratoire Informatique, Image et Interaction (L3i)
La Rochelle Université
Avenue Michel Crépeau
17042 La Rochelle cedex 1
l3i.univ-larochelle.fr
univ-larochelle.fr
✔️ @ApplyTime
Research Scholar - Just transitions to net zero carbon emissions | Deadline: 2 January
The EF Program is looking to recruit a Research Scholar with a strong background in quantitative empirical research for the “Just transitions to net zero carbon emissions for all” (JustTrans4All) project. The successful candidate will study factors supporting just energy transitions and explore potential implications for human wellbeing.
Background
The newly founded Economic Frontiers (EF) Program aspires to provide a comprehensive, rigorous and multidisciplinary framework for studying the changes to economic systems and behaviors that are required to shift production and consumption to patterns that are fair, sustainable and resilient. Explicit consideration will be given to
(i) Economics of equal life chances,
(ii) Economics of disruptive changes,
(iii) Economic governance of transitional change,
(iv) Economic development and wellbeing in a finite and interlinked world.
The program’s research integrates tightly with the natural, environmental, population, and systems science frameworks that IIASA is leading on, thus providing the multi-disciplinary approach needed for an understanding of the transition to sustainable, fair and resilient economies.
The position
The successful candidate will join the JustTrans4All project (project duration Sep 2021 – Dec 2023) and support the project team with the empirical analysis of drivers of just energy transitions and resulting implications for wellbeing using international micro and macro level data and innovative statistical and econometric methods.
The JustTrans4All project contributes to novel analyses of transition pathways that are socially and environmentally just. It will inform policy design aiming at achieving high levels of human wellbeing within planetary boundaries, in line with the UN 2030 Agenda and the Paris Agreement. As a collaborative effort of three research programs at IIASA (Economic Frontiers (EF), Energy, Climate, and Environment (ECE), Population and Just Societies (POPJUS)), the project aims at studying conditions that enable just transitions and developing a first comprehensive set of just transition scenarios towards a net-zero carbon society. For this, the interdisciplinary team combines soft-systems analysis approaches grounded in ethical reasoning with quantitative empirical and prospective modelling techniques.
As part of the empirical work package of the project, the incumbent will first support the collection of international longitudinal data on energy access and transitions as well as data on multidimensional poverty, inequality, decent living standards, and human wellbeing; second, the candidate will empirically investigate how different factors and conditions (with a focus on governance and human capital) influence just transitions to net zero carbon emissions and what their human wellbeing implications are; and third, the candidate will provide estimates and inputs that can be used to develop a set of prospective models and just transition scenarios to assess how alternative pathways can ensure fair energy transitions and an equal distribution of wellbeing over time and space. Fourth, ideally the candidate will also contribute to the modeling of the impact of transition-induced health gains relying on an economic burden of disease framework. JustTrans4All will enhance IIASA policy impact by providing guidance on designing policies for socio-ecological transformation that enjoy societal support and leave no one behind.
The EF Program is looking to recruit a Research Scholar with a strong background in quantitative empirical research for the “Just transitions to net zero carbon emissions for all” (JustTrans4All) project. The successful candidate will study factors supporting just energy transitions and explore potential implications for human wellbeing.
Background
The newly founded Economic Frontiers (EF) Program aspires to provide a comprehensive, rigorous and multidisciplinary framework for studying the changes to economic systems and behaviors that are required to shift production and consumption to patterns that are fair, sustainable and resilient. Explicit consideration will be given to
(i) Economics of equal life chances,
(ii) Economics of disruptive changes,
(iii) Economic governance of transitional change,
(iv) Economic development and wellbeing in a finite and interlinked world.
The program’s research integrates tightly with the natural, environmental, population, and systems science frameworks that IIASA is leading on, thus providing the multi-disciplinary approach needed for an understanding of the transition to sustainable, fair and resilient economies.
The position
The successful candidate will join the JustTrans4All project (project duration Sep 2021 – Dec 2023) and support the project team with the empirical analysis of drivers of just energy transitions and resulting implications for wellbeing using international micro and macro level data and innovative statistical and econometric methods.
The JustTrans4All project contributes to novel analyses of transition pathways that are socially and environmentally just. It will inform policy design aiming at achieving high levels of human wellbeing within planetary boundaries, in line with the UN 2030 Agenda and the Paris Agreement. As a collaborative effort of three research programs at IIASA (Economic Frontiers (EF), Energy, Climate, and Environment (ECE), Population and Just Societies (POPJUS)), the project aims at studying conditions that enable just transitions and developing a first comprehensive set of just transition scenarios towards a net-zero carbon society. For this, the interdisciplinary team combines soft-systems analysis approaches grounded in ethical reasoning with quantitative empirical and prospective modelling techniques.
As part of the empirical work package of the project, the incumbent will first support the collection of international longitudinal data on energy access and transitions as well as data on multidimensional poverty, inequality, decent living standards, and human wellbeing; second, the candidate will empirically investigate how different factors and conditions (with a focus on governance and human capital) influence just transitions to net zero carbon emissions and what their human wellbeing implications are; and third, the candidate will provide estimates and inputs that can be used to develop a set of prospective models and just transition scenarios to assess how alternative pathways can ensure fair energy transitions and an equal distribution of wellbeing over time and space. Fourth, ideally the candidate will also contribute to the modeling of the impact of transition-induced health gains relying on an economic burden of disease framework. JustTrans4All will enhance IIASA policy impact by providing guidance on designing policies for socio-ecological transformation that enjoy societal support and leave no one behind.
Main duties and responsibilities
Contribute actively to the research of the JustTrans4All Project, especially on topics related to the analysis of drivers of just energy transitions and the implications for wellbeing
Support the collection of relevant international data at the micro and macro level. Preparing and managing data sources for the project
Conduct statistical analyses on just energy transitions and wellbeing implications
Carry out research that advances the state-of-the-art on the topic, publish relevant results in peer-reviewed journals, and participate in scientific conferences and workshops
Actively engage with other researchers in the EF, POPJUS, and other IIASA programs, to establish joint research activities
In line with the team spirit that prevails at IIASA, the incumbent may occasionally work on other tasks assigned by their superiors, that might not be directly related to this appointment but where the post holder has relevant experience and skills, and/or a shortage of immediate personnel capabilities requires such.
Qualifications
PhD in demography, quantitative social sciences, statistics, economics, sociology or other related field(s) coupled with solid expertise and interest in the topic of just energy transitions
Proven competence in statistics/econometrics; experience with relevant statistical packages e.g., R, STATA and/or Python
Extensive empirical research experience in the social sciences, including demonstrated experience in developing research plans, collecting and managing data, and carrying out statistical analyses
Experience with data processing and handling of large-scale datasets at the micro and macro level. Preferably experience with georeferenced data
Track record in research and publication output corresponding to the career stage of the successful candidate
Excellent command of written and spoken English
Innovative and critical thinking. Proven independence in conducting research
Demonstrated willingness and ability to actively engage in collaboration within a multi-disciplinary environment
Willingness to engage with stakeholders in communicating and devising research, and to engage in capacity building efforts
IIASA offers an interdisciplinary and international workplace, and the possibility to interact with researchers of different nationalities, with strong ties to a world-wide network of research institutions engaged in environmental systems research. The successful candidate must be able to work in, and have respect for, an intercultural environment, and IIASA core values.
✔️ @ApplyTime
Contribute actively to the research of the JustTrans4All Project, especially on topics related to the analysis of drivers of just energy transitions and the implications for wellbeing
Support the collection of relevant international data at the micro and macro level. Preparing and managing data sources for the project
Conduct statistical analyses on just energy transitions and wellbeing implications
Carry out research that advances the state-of-the-art on the topic, publish relevant results in peer-reviewed journals, and participate in scientific conferences and workshops
Actively engage with other researchers in the EF, POPJUS, and other IIASA programs, to establish joint research activities
In line with the team spirit that prevails at IIASA, the incumbent may occasionally work on other tasks assigned by their superiors, that might not be directly related to this appointment but where the post holder has relevant experience and skills, and/or a shortage of immediate personnel capabilities requires such.
Qualifications
PhD in demography, quantitative social sciences, statistics, economics, sociology or other related field(s) coupled with solid expertise and interest in the topic of just energy transitions
Proven competence in statistics/econometrics; experience with relevant statistical packages e.g., R, STATA and/or Python
Extensive empirical research experience in the social sciences, including demonstrated experience in developing research plans, collecting and managing data, and carrying out statistical analyses
Experience with data processing and handling of large-scale datasets at the micro and macro level. Preferably experience with georeferenced data
Track record in research and publication output corresponding to the career stage of the successful candidate
Excellent command of written and spoken English
Innovative and critical thinking. Proven independence in conducting research
Demonstrated willingness and ability to actively engage in collaboration within a multi-disciplinary environment
Willingness to engage with stakeholders in communicating and devising research, and to engage in capacity building efforts
IIASA offers an interdisciplinary and international workplace, and the possibility to interact with researchers of different nationalities, with strong ties to a world-wide network of research institutions engaged in environmental systems research. The successful candidate must be able to work in, and have respect for, an intercultural environment, and IIASA core values.
✔️ @ApplyTime
Postdoc on AI for the Operating Room of the Future
The Visual Artificial Intelligence Laboratory at Oxford Brookes University, led by Professor Fabio Cuzzolin, is seeking a Postdoctoral Researcher in AI for the Operating Room of the Future, to be appointed as soon as possible after October 1st 2021, full-time, until December 31 2022.
The deadline for application is January 3rd 2022.
Salary: £32,817 rising annually to £35,845.
The Postdoc will lead the Lab’s efforts in the context of a new EPSRC Transformative Healthcare Technologies project entitled “MAESTRO Jr - Multi-sensing AI Environment for Surgical Task & Role Optimisation”, and led by Dr George Mylonas of Imperial College London.
The project’s overarching objective is to take radical steps towards the development of an AI-centred operating room of the 2050s. It envisages a smart operating room environment (which we term MAESTRO, in analogy with the way an orchestra conductor, a 'maestro', oversees, overhears and directs a group of people on a common task) powered by trustable, human-understanding artificial intelligence, able to continually adapt and learn the best way to optimise safety, efficacy, teamwork, economy, and clinical outcomes.
In particular the Postdoc will lead the work on multi-sensing situation awareness, event detection and automated checklisting, detection of cognitive overload in surgical staff, and continual learning for perception and decision making.
The Visual Artificial Intelligence Laboratory
https://cms.brookes.ac.uk/staff/FabioCuzzolin/
is a fast-growing research unit currently running on a budget of £3 million from nine live projects funded by the EU (2), Innovate UK (2), Leverhulme, Huawei, the British Council and others. We are leaders in the field of deep learning for action and event detection, but our research interests span artificial intelligence, uncertainty theory, machine learning, computer vision, autonomous driving, surgical and mobile robotics, AI for healthcare.
The Lab is currently pioneering frontier topics in AI such as machine theory of mind, self-supervised learning, continual learning and future event prediction. The Laboratory is part of the University’s new Institute for Ethical AI and is in the process of launching a new start-up to develop the world’s first AI-powered coaching app for competitive sports.
You will join a vibrant and fast growing team foreseen to comprise 35+ people in 2022. You will support Prof Cuzzolin in the overall management of the project. You will be working on a network of cutting edge 4-GPU and 8-GPU workstations, mentor PhD and MSc students and seek additional external funding to complement the Lab’s existing activities.
You are encouraged to contact Prof Cuzzolin at [email protected] for more information and an informal feedback on your application.
To formally apply, please follow the instructions provided here:
https://my.corehr.com/pls/oburecruit/erq_jobspec_details_form.jobspec?p_id=117337
✔️ @ApplyTime
The Visual Artificial Intelligence Laboratory at Oxford Brookes University, led by Professor Fabio Cuzzolin, is seeking a Postdoctoral Researcher in AI for the Operating Room of the Future, to be appointed as soon as possible after October 1st 2021, full-time, until December 31 2022.
The deadline for application is January 3rd 2022.
Salary: £32,817 rising annually to £35,845.
The Postdoc will lead the Lab’s efforts in the context of a new EPSRC Transformative Healthcare Technologies project entitled “MAESTRO Jr - Multi-sensing AI Environment for Surgical Task & Role Optimisation”, and led by Dr George Mylonas of Imperial College London.
The project’s overarching objective is to take radical steps towards the development of an AI-centred operating room of the 2050s. It envisages a smart operating room environment (which we term MAESTRO, in analogy with the way an orchestra conductor, a 'maestro', oversees, overhears and directs a group of people on a common task) powered by trustable, human-understanding artificial intelligence, able to continually adapt and learn the best way to optimise safety, efficacy, teamwork, economy, and clinical outcomes.
In particular the Postdoc will lead the work on multi-sensing situation awareness, event detection and automated checklisting, detection of cognitive overload in surgical staff, and continual learning for perception and decision making.
The Visual Artificial Intelligence Laboratory
https://cms.brookes.ac.uk/staff/FabioCuzzolin/
is a fast-growing research unit currently running on a budget of £3 million from nine live projects funded by the EU (2), Innovate UK (2), Leverhulme, Huawei, the British Council and others. We are leaders in the field of deep learning for action and event detection, but our research interests span artificial intelligence, uncertainty theory, machine learning, computer vision, autonomous driving, surgical and mobile robotics, AI for healthcare.
The Lab is currently pioneering frontier topics in AI such as machine theory of mind, self-supervised learning, continual learning and future event prediction. The Laboratory is part of the University’s new Institute for Ethical AI and is in the process of launching a new start-up to develop the world’s first AI-powered coaching app for competitive sports.
You will join a vibrant and fast growing team foreseen to comprise 35+ people in 2022. You will support Prof Cuzzolin in the overall management of the project. You will be working on a network of cutting edge 4-GPU and 8-GPU workstations, mentor PhD and MSc students and seek additional external funding to complement the Lab’s existing activities.
You are encouraged to contact Prof Cuzzolin at [email protected] for more information and an informal feedback on your application.
To formally apply, please follow the instructions provided here:
https://my.corehr.com/pls/oburecruit/erq_jobspec_details_form.jobspec?p_id=117337
✔️ @ApplyTime
Research Fellowships at Northeastern University
We are accepting applications for our new Research Fellowship program. This is a fully funded 1-2 year program to allow new PhDs to focus on research before transitioning to a tenure-track Assistant Professor position at Northeastern. It is a great opportunity for people that want a bit more experience and mentoring before starting a tenure track job. We are particularly interested in candidates who are traditionally underrepresented in computing and higher education. More details can be found at the link below.
https://www.khoury.northeastern.edu/research/fellowship/
Christopher Amato
Assistant Professor
Khoury College of Computer Sciences
Northeastern University
https://www.ccs.neu.edu/home/camato/
✔️ @ApplyTime
We are accepting applications for our new Research Fellowship program. This is a fully funded 1-2 year program to allow new PhDs to focus on research before transitioning to a tenure-track Assistant Professor position at Northeastern. It is a great opportunity for people that want a bit more experience and mentoring before starting a tenure track job. We are particularly interested in candidates who are traditionally underrepresented in computing and higher education. More details can be found at the link below.
https://www.khoury.northeastern.edu/research/fellowship/
Christopher Amato
Assistant Professor
Khoury College of Computer Sciences
Northeastern University
https://www.ccs.neu.edu/home/camato/
✔️ @ApplyTime
Postdoctoral Fellow on Machine Learning for Energy Forecasting at Basque Center for Applied Mathematics
New Postdoctoral Fellow on Machine Learning for Energy Forecasting
This work is framed in IA4TES – Inteligencia Artifical para la Transición Energética Sostenible project. This offer, in particular, is to work in Machine Learning group at Basque Center for Applied Mathematics, where Machine Learning for Energy Forecasting topic will be worked.
Deadline of application: December 10, 2021
Applications must be submitted on-line at: https://www.bcamath.org/en/research/job/ic2021-11-postdoctoral-fellow-on-machine-learning-for-energy-forecasting
Requirement: Applicants must have their PhD completed before the contract starts
Skills:
Good interpersonal skills.
A proven track record in quality research, as evidenced by research publications in top scientific journals and conferences.
Demonstrated ability to work independently and as part of a collaborative research team.
Ability to present and publish research outcomes in spoken (talks) and written (papers) form.
Ability to effectively communicate and present research ideas to researchers and stakeholders with different backgrounds.
Fluency in spoken and written Spanish and English.
The preferred candidate will have: Strong background in mathematics/statistics. Strong background in data science/machine learning. Background in time series prediction. Background in energy-related applications such as load forecasting. Good programming skills in Python and/or Matlab. Interest and disposition to work in interdisciplinary groups and collaborate with multiple companies/institutions.
✔️ @ApplyTime
New Postdoctoral Fellow on Machine Learning for Energy Forecasting
This work is framed in IA4TES – Inteligencia Artifical para la Transición Energética Sostenible project. This offer, in particular, is to work in Machine Learning group at Basque Center for Applied Mathematics, where Machine Learning for Energy Forecasting topic will be worked.
Deadline of application: December 10, 2021
Applications must be submitted on-line at: https://www.bcamath.org/en/research/job/ic2021-11-postdoctoral-fellow-on-machine-learning-for-energy-forecasting
Requirement: Applicants must have their PhD completed before the contract starts
Skills:
Good interpersonal skills.
A proven track record in quality research, as evidenced by research publications in top scientific journals and conferences.
Demonstrated ability to work independently and as part of a collaborative research team.
Ability to present and publish research outcomes in spoken (talks) and written (papers) form.
Ability to effectively communicate and present research ideas to researchers and stakeholders with different backgrounds.
Fluency in spoken and written Spanish and English.
The preferred candidate will have: Strong background in mathematics/statistics. Strong background in data science/machine learning. Background in time series prediction. Background in energy-related applications such as load forecasting. Good programming skills in Python and/or Matlab. Interest and disposition to work in interdisciplinary groups and collaborate with multiple companies/institutions.
✔️ @ApplyTime
www.bcamath.org
Call Postdoctoral Fellowship - BCAM - Basque Center for Applied Mathematics
Call Post Doc
Postdoctoral Associate in Child Psychopathology at Yale Child Study Center
We are seeking an exceptional, motivated, and creative Postdoctoral Associate to be involved in prospective studies of infants with elevated likelihood for Autism Spectrum Disorders (ASD) as well as toddlers with ASD. The Associate will join an interdisciplinary research team at the Social and Affective Neuroscience of Autism Program: https://medicine.yale.edu/lab/chawarska/.
The postdoctoral associate will work as part of the Yale Autism Center of Excellence (ACE) Program Project (ace.yale.edu) team at the Yale Child Study Center (CSC) led by Prof. Chawarska. The Yale NIH ACE Research project represents a joint effort across child psychiatry, pediatrics, radiology, and statistics and data science departments at Yale. The ACE project aims to identify prenatal and neonatal brain processes contributing to development of autism.
During the two-year postdoctoral program, the associate will be expected to lead and participate in the development and implementation of novel eye-tracking, MRI, fNIRS, and behavioral protocols targeting early markers of core and co-occurring features in autism. The postdoctoral associate will also be expected to take a leadership role on data analysis and manuscript preparation based on the extensive data collection through the ACE and SANA research programs. The postdoctoral associate will train and supervise research staff and students and assist with data management. Other responsibilities may include assisting with behavioral, physiological and neuroimaging studies as well as in grant writing. Candidates with a strong methodological background, statistical skills, expertise in eye-tracking, MRI, and fNIRS, as well as in programming, excellent communication skills, and a strong publication record will be reviewed favorably.
Anticipated start date is July 1, 2022. The priority application deadline is January 15, 2022. Please visit our lab website for application instructions and more information about the position: https://medicine.yale.edu/lab/chawarska/jobs/psychology/
Position Category: Postdoctoral
Name of Lab: Yale Social and Affective Neuroscience of Autism (SANA) Program
Name of Supervisor: Katarzyna Chawarska, PhD
Closing Date: Open until filled (priority deadline: January 15, 2022)
Emma Brennan-Wydra, MSI
Pronouns: she/her/hers [what’s this?]
Data Manager, Social and Affective Neuroscience of Autism Program
Yale Child Study Center
c: 617-306-7350 | e: [email protected]
✔️ @ApplyTime
We are seeking an exceptional, motivated, and creative Postdoctoral Associate to be involved in prospective studies of infants with elevated likelihood for Autism Spectrum Disorders (ASD) as well as toddlers with ASD. The Associate will join an interdisciplinary research team at the Social and Affective Neuroscience of Autism Program: https://medicine.yale.edu/lab/chawarska/.
The postdoctoral associate will work as part of the Yale Autism Center of Excellence (ACE) Program Project (ace.yale.edu) team at the Yale Child Study Center (CSC) led by Prof. Chawarska. The Yale NIH ACE Research project represents a joint effort across child psychiatry, pediatrics, radiology, and statistics and data science departments at Yale. The ACE project aims to identify prenatal and neonatal brain processes contributing to development of autism.
During the two-year postdoctoral program, the associate will be expected to lead and participate in the development and implementation of novel eye-tracking, MRI, fNIRS, and behavioral protocols targeting early markers of core and co-occurring features in autism. The postdoctoral associate will also be expected to take a leadership role on data analysis and manuscript preparation based on the extensive data collection through the ACE and SANA research programs. The postdoctoral associate will train and supervise research staff and students and assist with data management. Other responsibilities may include assisting with behavioral, physiological and neuroimaging studies as well as in grant writing. Candidates with a strong methodological background, statistical skills, expertise in eye-tracking, MRI, and fNIRS, as well as in programming, excellent communication skills, and a strong publication record will be reviewed favorably.
Anticipated start date is July 1, 2022. The priority application deadline is January 15, 2022. Please visit our lab website for application instructions and more information about the position: https://medicine.yale.edu/lab/chawarska/jobs/psychology/
Position Category: Postdoctoral
Name of Lab: Yale Social and Affective Neuroscience of Autism (SANA) Program
Name of Supervisor: Katarzyna Chawarska, PhD
Closing Date: Open until filled (priority deadline: January 15, 2022)
Emma Brennan-Wydra, MSI
Pronouns: she/her/hers [what’s this?]
Data Manager, Social and Affective Neuroscience of Autism Program
Yale Child Study Center
c: 617-306-7350 | e: [email protected]
✔️ @ApplyTime
Chawarska Lab
Yale Social and Affective Neuroscience of Autism Program (SANA)
Work in our lab is focused on early social and affective development of children with Autism Spectrum Disorder (ASD) and other disabilities. We aim to discover
Postdoc on Document Analysis & Recognition at NC State University, USA
Dear all,
We have a postdoc opening on developing Arabic handwritten text recognition systems at the NC State University, North Carolina, USA.
No Arabic knowledge is needed but please make sure that you are good at deep learning and you are in one of the following fields: document analysis, computer vision, and image processing. You will be jointly supervised by a humanity faculty member and an ECE faculty member (me).
More details about the opening including the application link can be found here:
https://jobs.ncsu.edu/postings/152807
If you have any questions, please don't hesitate to let me know. I also highly appreciate it if you could forward this opening to relevant parties.
Sincerely,
Chau-Wai Wong
Assistant Professor
ECE, NC State University
✔️ @ApplyTime
Dear all,
We have a postdoc opening on developing Arabic handwritten text recognition systems at the NC State University, North Carolina, USA.
No Arabic knowledge is needed but please make sure that you are good at deep learning and you are in one of the following fields: document analysis, computer vision, and image processing. You will be jointly supervised by a humanity faculty member and an ECE faculty member (me).
More details about the opening including the application link can be found here:
https://jobs.ncsu.edu/postings/152807
If you have any questions, please don't hesitate to let me know. I also highly appreciate it if you could forward this opening to relevant parties.
Sincerely,
Chau-Wai Wong
Assistant Professor
ECE, NC State University
✔️ @ApplyTime
Postdoc on vision-based human body-tracking for healthcare applications (Brest, France)
Topic: Vision-based human body-tracking for healthcare applications
Domain: Computer Vision (Computer Science, Artificial Intelligence)
Project: ECFvisuL
Contract duration: 18 months
Geographic location: Brest, France
Department: RAMBO team, Computer Science Department, IMT Atlantique
Minimum degree required: Doctorate (PhD)
Starting date: As soon as possible, 1 January 2023 at latest
Gross annual salary: Between 34 400 € and 35 650 € (depending on your experience)
Application deadline: 31 January 2022
Apply here: https://institutminestelecom.recruitee.com/o/postdoctorant-intelligence-artificielle-vision-par-ordinateur-fh-cdd-18-mois
1. ENVIRONMENT
The postdoctorate will be located at IMT Atlantique, on its Brest campus, in the RAMBO team [1] (member of Lab-STICC laboratory, mixed research unit of CNRS #6285) and supervised by the associate professors Mihai Andries [2] and Panagiotis Papadakis [3]. The research domains of the RAMBO team are Cognitive Robotics, Robot Learning, Ambient assisted living and Human-robot interaction. The team possesses a LivingLab for e-Health/Smart Living Experiment'HAAL [4], equipped with sensors for tracking human activity, where experiments related to the project can be performed, as well as a GERT ageing simulator.
This project is part of the RAMBO research activities on ageing-at-home and is complementary to our ongoing research on the recognition of activities of daily living (ADL).
[1] https://www.imt-atlantique.fr/en/research-innovation/teams/research-team-rambo
[2] https://mihai.andries.eu/
[3] https://sites.google.com/site/pgpapadakis
[4] https://www.imt-atlantique.fr/sites/default/files/recherche/plateformes/en/experiment_haal.pdf
2. MISSION
Functional capacity evaluation (FCE) is a set of dynamical tests consisting of functional evaluations (sitting, kneeling, standing, bending, climbing a staircase, grasping an object, lifting, carrying, etc.) which provide information on the capacity of a person do act in a work environment. FCE is currently used by employers and medical professionals to decide when an employee is ready to return to work but it can be more broadly used as an indicator of human musculoskeletal health.
We propose to develop an automatic solution for continuous FCE in a domestic environment on the basis of a Computer Vision system for tracking human body posture. Such a system would acquire more temporal data on the musculoskeletal capacity of a human than a typical doctor during an FCE session, producing more robust evaluation results.
3. SKILLS AND ABILITIES:
Knowledge:
Required:
* know statistics;
* know machine learning techniques for human-body posture recognition;
* know English Language (B2 level at least).
Desirable:
* know the scientific literature on musculoskeletal disorders;
* know how to conceive experiments on physical capacity evaluation;
* know how to write scientific articles.
Competences :
Required:
* apply machine learning techniques for human activity recognition;
* apply machine learning techniques for visual estimation of carried weight;
* present your research work to a scientific audience, as well as to the general public.
Desirable:
* use a 3D motion capture device (like Optitrack);
* use software for visual recognition of human-body posture (like MargiPose or Skeleton Tracking SDK);
* use inertial sensors.
Personal traits:
* be able to work in a team;
* be able to communicate regularly with your colleagues and supervisors.
4. HOW TO SUBMIT YOUR APPLICATION ?
Please submit your application through the Recruitee [5] system.
[5] https://institutminestelecom.recruitee.com/o/postdoctorant-intelligence-artificielle-vision-par-ordinateur-fh-cdd-18-mois
Topic: Vision-based human body-tracking for healthcare applications
Domain: Computer Vision (Computer Science, Artificial Intelligence)
Project: ECFvisuL
Contract duration: 18 months
Geographic location: Brest, France
Department: RAMBO team, Computer Science Department, IMT Atlantique
Minimum degree required: Doctorate (PhD)
Starting date: As soon as possible, 1 January 2023 at latest
Gross annual salary: Between 34 400 € and 35 650 € (depending on your experience)
Application deadline: 31 January 2022
Apply here: https://institutminestelecom.recruitee.com/o/postdoctorant-intelligence-artificielle-vision-par-ordinateur-fh-cdd-18-mois
1. ENVIRONMENT
The postdoctorate will be located at IMT Atlantique, on its Brest campus, in the RAMBO team [1] (member of Lab-STICC laboratory, mixed research unit of CNRS #6285) and supervised by the associate professors Mihai Andries [2] and Panagiotis Papadakis [3]. The research domains of the RAMBO team are Cognitive Robotics, Robot Learning, Ambient assisted living and Human-robot interaction. The team possesses a LivingLab for e-Health/Smart Living Experiment'HAAL [4], equipped with sensors for tracking human activity, where experiments related to the project can be performed, as well as a GERT ageing simulator.
This project is part of the RAMBO research activities on ageing-at-home and is complementary to our ongoing research on the recognition of activities of daily living (ADL).
[1] https://www.imt-atlantique.fr/en/research-innovation/teams/research-team-rambo
[2] https://mihai.andries.eu/
[3] https://sites.google.com/site/pgpapadakis
[4] https://www.imt-atlantique.fr/sites/default/files/recherche/plateformes/en/experiment_haal.pdf
2. MISSION
Functional capacity evaluation (FCE) is a set of dynamical tests consisting of functional evaluations (sitting, kneeling, standing, bending, climbing a staircase, grasping an object, lifting, carrying, etc.) which provide information on the capacity of a person do act in a work environment. FCE is currently used by employers and medical professionals to decide when an employee is ready to return to work but it can be more broadly used as an indicator of human musculoskeletal health.
We propose to develop an automatic solution for continuous FCE in a domestic environment on the basis of a Computer Vision system for tracking human body posture. Such a system would acquire more temporal data on the musculoskeletal capacity of a human than a typical doctor during an FCE session, producing more robust evaluation results.
3. SKILLS AND ABILITIES:
Knowledge:
Required:
* know statistics;
* know machine learning techniques for human-body posture recognition;
* know English Language (B2 level at least).
Desirable:
* know the scientific literature on musculoskeletal disorders;
* know how to conceive experiments on physical capacity evaluation;
* know how to write scientific articles.
Competences :
Required:
* apply machine learning techniques for human activity recognition;
* apply machine learning techniques for visual estimation of carried weight;
* present your research work to a scientific audience, as well as to the general public.
Desirable:
* use a 3D motion capture device (like Optitrack);
* use software for visual recognition of human-body posture (like MargiPose or Skeleton Tracking SDK);
* use inertial sensors.
Personal traits:
* be able to work in a team;
* be able to communicate regularly with your colleagues and supervisors.
4. HOW TO SUBMIT YOUR APPLICATION ?
Please submit your application through the Recruitee [5] system.
[5] https://institutminestelecom.recruitee.com/o/postdoctorant-intelligence-artificielle-vision-par-ordinateur-fh-cdd-18-mois
Institut Mines-Télécom
Careers - Jobs - Institut Mines-Télécom
You will need:
* your CV,
* a motivation letter,
* a copy of your doctorate diploma, and
* contact details of two referees.
Eligibility criteria apply regarding candidate's mobility: the postdoctoral candidate must have spent at least 18 months outside of France between 1 May 2018 and the contract starting date.
Applications will be processed on a continuous basis.
The deadline for submitting your application is 31 January 2022 .
For any questions regarding this position, please contact Mihai Andries at [email protected]
5. REFERENCES
* Devanne, Maxime, and Panagiotis Papadakis.
"Recognition of activities of daily living via hierarchical long-short term memory networks."
In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 3318-3324. IEEE, 2019.
https://ieeexplore.ieee.org/document/8914457
* C. Le Bono, P. Papadakis, C. Buche,
Assessment of Conformal Use of Personal Protective Equipment by Object and Human Pose Recognition,
IEEE International Conference on Safety, Security and Rescue Robotics (SSRR), 2020
https://hal-imt-atlantique.archives-ouvertes.fr/hal-03001159/document
* Andries, Mihai.
"Object and human tracking, and robot control through a load sensing floor."
PhD diss., Université de Lorraine, 2015.
https://hal.inria.fr/tel-01252938/file/thesis.pdf
6. BREST
Brest is a middle-sized town on the French Atlantic coast, home to a population of nearly 140 thousand people in 2018. Located near the western tip of the Brittany peninsula, it has a temperate oceanic climate, with mild summers and wet winters.
Almost entirely destroyed during WW2, the city center was rebuilt in Art Deco style. Historical monuments include the Brest castle, the Tanguy tower, and the Saint-Louis church. Gastronomically, Brittany is known for its galettes, crêpes, the Far breton and the Kouign Amann. Profiting from its beautiful coastline, Brest offers plenty of summer water activities. The Blancs Sablons beach, popular among the locals, is only 25 minutes away by car. The picturesque GR34 coastline trail [6] is famous among hikers.
Brest hosts offices of Naval Group, THALES, Dassault Systemes, Ifremer, Université Bretagne occidentale and IMT Atlantique, among others. Brest is connected by high-speed rail to Rennes (2h) and Paris (3h45). The Brest international airport [7] offers direct flights to Lisbon and Porto, Majorca, and Heraklion in Greece, as well as to national destinations like Nice, Lyon, and Toulouse.
[6] https://en.wikipedia.org/wiki/GR_34
[7] https://www.brest.aeroport.bzh/accueil
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* your CV,
* a motivation letter,
* a copy of your doctorate diploma, and
* contact details of two referees.
Eligibility criteria apply regarding candidate's mobility: the postdoctoral candidate must have spent at least 18 months outside of France between 1 May 2018 and the contract starting date.
Applications will be processed on a continuous basis.
The deadline for submitting your application is 31 January 2022 .
For any questions regarding this position, please contact Mihai Andries at [email protected]
5. REFERENCES
* Devanne, Maxime, and Panagiotis Papadakis.
"Recognition of activities of daily living via hierarchical long-short term memory networks."
In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 3318-3324. IEEE, 2019.
https://ieeexplore.ieee.org/document/8914457
* C. Le Bono, P. Papadakis, C. Buche,
Assessment of Conformal Use of Personal Protective Equipment by Object and Human Pose Recognition,
IEEE International Conference on Safety, Security and Rescue Robotics (SSRR), 2020
https://hal-imt-atlantique.archives-ouvertes.fr/hal-03001159/document
* Andries, Mihai.
"Object and human tracking, and robot control through a load sensing floor."
PhD diss., Université de Lorraine, 2015.
https://hal.inria.fr/tel-01252938/file/thesis.pdf
6. BREST
Brest is a middle-sized town on the French Atlantic coast, home to a population of nearly 140 thousand people in 2018. Located near the western tip of the Brittany peninsula, it has a temperate oceanic climate, with mild summers and wet winters.
Almost entirely destroyed during WW2, the city center was rebuilt in Art Deco style. Historical monuments include the Brest castle, the Tanguy tower, and the Saint-Louis church. Gastronomically, Brittany is known for its galettes, crêpes, the Far breton and the Kouign Amann. Profiting from its beautiful coastline, Brest offers plenty of summer water activities. The Blancs Sablons beach, popular among the locals, is only 25 minutes away by car. The picturesque GR34 coastline trail [6] is famous among hikers.
Brest hosts offices of Naval Group, THALES, Dassault Systemes, Ifremer, Université Bretagne occidentale and IMT Atlantique, among others. Brest is connected by high-speed rail to Rennes (2h) and Paris (3h45). The Brest international airport [7] offers direct flights to Lisbon and Porto, Majorca, and Heraklion in Greece, as well as to national destinations like Nice, Lyon, and Toulouse.
[6] https://en.wikipedia.org/wiki/GR_34
[7] https://www.brest.aeroport.bzh/accueil
✔️ @ApplyTime
ieeexplore.ieee.org
Recognition of Activities of Daily Living via Hierarchical Long-Short Term Memory Networks
In order to offer optimal and personalized assistance services to frail people, smart homes or assistive robots must be able to understand the context and activities of users. With this outlook, we propose a vision-based approach for understanding activities…
Post doctoral position on time series analysis of,data living on the SPD manifold
We are seeking an outstanding postdoctoral research fellow with experience in deep learning / machine learning to work with us at Caen University, France during one year on a project investigating the analysis of time series of data corresponding to SPD matrices. The challenge here will be to define machine learning methods and more specifically deep learning methods (either convolutional or recursive) to analyze these data by using all the interesting properties of this specific manifold.
Context
The postdoctoral position is funded for one year under the research project PredictAlert supported by the Region Normandy (France). The PredictAlert project gathers engineering schools and universities around the design of a better understanding of the brain states during different states of wakefulness.
Objectives and challenges
The project is based on data from a cohort being currently acquired. It includes EEG and MRI acquisitions performed while subjects are falling asleep for a nap. In both cases, an acquisition in a given time window, is characterized by a SPD matrix. Each entry of this matrix correspond either to a correlation between two sensors in the case of an EEG acquisition or a correlation between two brain’s zones in the case of an IRM acquisition.
In a first step the candidate will have to work on EEG acquisitions in order to design a deep learning algorithm predicting quantified levels of wakefulness along long EEG sequences. Convolutional [1, 3] or recurrent [2, 4] networks on the SPD manifold will be both studded and evaluated before a focus on the more promising approach.
While functional IRM sequences may also be characterized as time series of SPD matrices, these sequences are based on data with a much better spatial resolution than EEGs. This come at the price of a much lower temporal resolution compared EEG acquisitions. The candidate will have to adapt the work already done on EEG data to functional IRM datum and to compare both results.
Candidate profile
The candidate must have a recent Ph.D. (within 5 years) in Computer science (or Applied Mathematics) in the field of Machine Learning.
Knowledge and experience within Deep Learning frameworks is highly recommended.
The candidate will perform research and algorithmic developments and solid programming skills are required.
Interpersonal skills and the ability to work well individually or as a member of a project team are recommended.
Good written and verbal communication skills are required, the candidate has to be fluent in spoken French or English and written English. Working language can be English or French.
Location
Caen, France in the GREYC UMR CNRS laboratory. Situated in the Normandy region of France close to the sea and about 240km west of Paris the city still has many old quarters, a population of around 120,000 the city area has roughly 250,000 inhabitants. Some photos
Application
Interested candidates should submit their application to
[email protected] and
[email protected]
Please include in your application email one Curriculum Vitae, one statement of research letter explaining your interest and your skills for this position, and 2 reference letters (all in a single PDF file). Applications will be admitted until the position is filled.
Additional information
Host institution: ENSICAEN, University of Caen Normandy and CNRS, GREYC laboratory (UMR 6072)
Gross Salary: between 2339 and 3268 euros per month according to experience (charges included)
Duration: 12 months.
Starting date: from January 2020
Advantages: Possibility of French courses, participation in transport costs, possibility of restoration on site.
References
We are seeking an outstanding postdoctoral research fellow with experience in deep learning / machine learning to work with us at Caen University, France during one year on a project investigating the analysis of time series of data corresponding to SPD matrices. The challenge here will be to define machine learning methods and more specifically deep learning methods (either convolutional or recursive) to analyze these data by using all the interesting properties of this specific manifold.
Context
The postdoctoral position is funded for one year under the research project PredictAlert supported by the Region Normandy (France). The PredictAlert project gathers engineering schools and universities around the design of a better understanding of the brain states during different states of wakefulness.
Objectives and challenges
The project is based on data from a cohort being currently acquired. It includes EEG and MRI acquisitions performed while subjects are falling asleep for a nap. In both cases, an acquisition in a given time window, is characterized by a SPD matrix. Each entry of this matrix correspond either to a correlation between two sensors in the case of an EEG acquisition or a correlation between two brain’s zones in the case of an IRM acquisition.
In a first step the candidate will have to work on EEG acquisitions in order to design a deep learning algorithm predicting quantified levels of wakefulness along long EEG sequences. Convolutional [1, 3] or recurrent [2, 4] networks on the SPD manifold will be both studded and evaluated before a focus on the more promising approach.
While functional IRM sequences may also be characterized as time series of SPD matrices, these sequences are based on data with a much better spatial resolution than EEGs. This come at the price of a much lower temporal resolution compared EEG acquisitions. The candidate will have to adapt the work already done on EEG data to functional IRM datum and to compare both results.
Candidate profile
The candidate must have a recent Ph.D. (within 5 years) in Computer science (or Applied Mathematics) in the field of Machine Learning.
Knowledge and experience within Deep Learning frameworks is highly recommended.
The candidate will perform research and algorithmic developments and solid programming skills are required.
Interpersonal skills and the ability to work well individually or as a member of a project team are recommended.
Good written and verbal communication skills are required, the candidate has to be fluent in spoken French or English and written English. Working language can be English or French.
Location
Caen, France in the GREYC UMR CNRS laboratory. Situated in the Normandy region of France close to the sea and about 240km west of Paris the city still has many old quarters, a population of around 120,000 the city area has roughly 250,000 inhabitants. Some photos
Application
Interested candidates should submit their application to
[email protected] and
[email protected]
Please include in your application email one Curriculum Vitae, one statement of research letter explaining your interest and your skills for this position, and 2 reference letters (all in a single PDF file). Applications will be admitted until the position is filled.
Additional information
Host institution: ENSICAEN, University of Caen Normandy and CNRS, GREYC laboratory (UMR 6072)
Gross Salary: between 2339 and 3268 euros per month according to experience (charges included)
Duration: 12 months.
Starting date: from January 2020
Advantages: Possibility of French courses, participation in transport costs, possibility of restoration on site.
References
[1] Rudrasis Chakraborty, Jose Bouza, Jonathan Manton, and Baba C Vemuri. Manifoldnet: A deep neural network for manifold-valued data with appli-
cations. IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 1–1, 2020.
[2] Rudrasis Chakraborty, Chun-Hao Yang, Xingjian Zhen, Monami Banerjee, Derek Archer, David Vaillancourt, Vikas Singh, and Baba Vemuri. A statistical recurrent model on the manifold of symmetric positive definite matrices. In S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 31. Curran Associates, Inc., 2018.
[3] Xuan Son Nguyen, Luc Brun, Olivier Lezoray, and Sébastien Bougleux. A neural network based on SPD manifold learning for skeleton-based hand
gesture recognition. In IEEE Conference on Computer Vision and Pattern Regognition (CVPR), Long Beach, United States, 2019.
[4] Xuan Son Nguyen, Luc Brun, Olivier Lézoray, and Sébastien Bougleux. Learning Recurrent High-order Statistics for Skeleton-based Hand Gesture Recognition. In International Conference on Pattern Recognition (ICPR -IEEE), Milan (virtual), Italy, 2021.
✔️ @ApplyTime
cations. IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 1–1, 2020.
[2] Rudrasis Chakraborty, Chun-Hao Yang, Xingjian Zhen, Monami Banerjee, Derek Archer, David Vaillancourt, Vikas Singh, and Baba Vemuri. A statistical recurrent model on the manifold of symmetric positive definite matrices. In S. Bengio, H. Wallach, H. Larochelle, K. Grauman, N. Cesa-Bianchi, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 31. Curran Associates, Inc., 2018.
[3] Xuan Son Nguyen, Luc Brun, Olivier Lezoray, and Sébastien Bougleux. A neural network based on SPD manifold learning for skeleton-based hand
gesture recognition. In IEEE Conference on Computer Vision and Pattern Regognition (CVPR), Long Beach, United States, 2019.
[4] Xuan Son Nguyen, Luc Brun, Olivier Lézoray, and Sébastien Bougleux. Learning Recurrent High-order Statistics for Skeleton-based Hand Gesture Recognition. In International Conference on Pattern Recognition (ICPR -IEEE), Milan (virtual), Italy, 2021.
✔️ @ApplyTime
Ph.D. Position: Machine Learning in Audio, TU Ilmenau, Germany
The Applied Media Systems group of Ilmenau University of Technology in Ilmenau, Germany, is looking for candidates for a half-time Ph.D position (20 hours/week), in the area of machine learning for audio. The duties include teaching seminars and supervising students in Media Technology and Electrical Engineering.
Duration: starting with 3 years, can be extended up to 6 years.
Starting date: February 1st, 2022.
Our group works on audio coding, filter banks, autoencoders, stochastic optimization, audio and musical source separation.
The ideal candidate will have solid knowledge in digital signal processing and machine learning for audio and video.
Requirement: Master's in electrical engineering or similar, with focus on digital signal processing and/or machine learning for audio and/or video.
Essential is curiosity for learning, ideas, and ingenuity.
If you are interested, send me an email, with a few of your main achievements:
[email protected]
The official applications link is:
https://jobundkarriere.tu-ilmenau.de/jobposting/f8e166014bb5382777de6fee7cb10d877f98a70b0
Our groups website is:
https://www.tu-ilmenau.de/mt-ams
Many greetings,
Gerald Schuller
✔️ @ApplyTime
The Applied Media Systems group of Ilmenau University of Technology in Ilmenau, Germany, is looking for candidates for a half-time Ph.D position (20 hours/week), in the area of machine learning for audio. The duties include teaching seminars and supervising students in Media Technology and Electrical Engineering.
Duration: starting with 3 years, can be extended up to 6 years.
Starting date: February 1st, 2022.
Our group works on audio coding, filter banks, autoencoders, stochastic optimization, audio and musical source separation.
The ideal candidate will have solid knowledge in digital signal processing and machine learning for audio and video.
Requirement: Master's in electrical engineering or similar, with focus on digital signal processing and/or machine learning for audio and/or video.
Essential is curiosity for learning, ideas, and ingenuity.
If you are interested, send me an email, with a few of your main achievements:
[email protected]
The official applications link is:
https://jobundkarriere.tu-ilmenau.de/jobposting/f8e166014bb5382777de6fee7cb10d877f98a70b0
Our groups website is:
https://www.tu-ilmenau.de/mt-ams
Many greetings,
Gerald Schuller
✔️ @ApplyTime