The Cologne Graduate School in Management, Economics, and Social Sciences (CGS) offers one Doctoral Scholarship in Business Administration (three years, starting October 1, 2022).



The Cologne Graduate School in Management, Economics and Social Sciences (CGS) at the University of Cologne (UoC) offers one three-year doctoral scholarship to outstanding students holding a Master’s degree (or equivalent) in Business Administration, Economics, Computer Science, Information Systems or Statistics.



The scholarship is integrated into the newly created initiative Analytics and Transformation. This initiative brings together researchers from different disciplines to work on research projects at the intersection of analytics, artificial intelligence, entrepreneurship, and innovation. Within the initiative we cover substantive topics that include marketing analytics, health, digital markets, digital innovation, digital transformation, and others.



The scholarship holder will be working closely with the principal researchers and will have the opportunity to participate in research seminars, workshops, and soft-skill courses. Moreover, they will be part of a vibrant and international research network centered around the Marketing, Information Systems, Operations, and Corporate Development.



About the Program

The scholarship holder will be enrolled in the Management doctoral track of the CGS of the Faculty of Management, Economics and Social Sciences (WiSo). The course program will start in October 2022. During the first year, students will take part in courses on multidisciplinary methods and theories, as well as subject-specific courses. Courses are taught in English. During the second and third year, students mainly conduct research and work on their thesis.



Qualifications

We are inviting applications by highly qualified graduates from Business Administration, Economics, Computer Science, Information Systems or Statistics. Candidates must hold a Master’s degree (or equivalent) or be very close to completion. We are looking for individuals who have demonstrated ability to work with business and social science data and who are confident in working with statistical software (e.g., R) and programming for analytics (e.g., Python, in particular with libraries such as scikit-learn, pandas, Keras, NumPy, or pyTorch).



Scholarships

The scholarship amounts to 1,365€ per month plus a yearly research budget of 1,000€. The scholarship is awarded for a maximum period of three years and is tax-free.



Application Procedure

Application is online only. The deadline for the submission of your application is March 1, 2022. For further information about the CGS please visit the School’s website. For more information on the application process and application documents, please visit the section on scholarship application.



Contact:

Dr. Katharina Laske ([email protected])



Best regards,

Christoph

Postdoctoral Research Associate in Machine Learning for Medical Image Analysis at University of Sheffield
for Medical Image Analysis to join our team at University of Sheffield, with a fixed term till 31st March 2023 and a start date as soon as possible.

See details and apply at Data Overview: Job Posting (shef.ac.uk)
Deadline: 12th Jan 2022.

Haiping Lu
--
Senior Lecturer in Machine Learning
Department of Computer Science
University of Sheffield

Optical Biology PhD Program at UCL (deadline extended to 20 December)
We invite applications for the Optical Biology 4-year PhD program at UCL.



This program brings together neuroscientists, cell biologists, physicists, chemists and computational scientists at UCL, with world-leading industrial and academic partners, to deliver an integrated training programme in the most advanced optical methods and analysis tools. The program offers a strong focus on bespoke personal mentorship and career development support for students.



Full funding will be available for top-ranked applicants; research expenses will also be provided, as well as funds to attend international courses and meetings. We also provide transition costs at the end of the PhD to help you move to the next stage of your career.



The EXTENDED application deadline is Monday 20 December 2022.



For more details and information about applying please visit:



https://opticalbiology.org



Applications and queries should be sent to:



[email protected]





—

Michael Hausser

Director, Optical Biology PhD Program

Facilitator, International Brain Laboratory

Professor of Neuroscience, UCL



tel +44-20-7679-6756

email [email protected]

Postdoc position for 2 years in Aarhus University (Denmark) to work on the gut-brain axis
Hello,

I am hiring a postdoc for my new lab for a 2 years position in beautiful Aarhus. Come join me in studying the enteric nervous system of Zebrafish in a brand new building and lab. I you're interested in light-sheet microscopy, the enteric nervous system, gut-brain axis or the microbiome don't hesitate to get in touch.

More information, and how to apply can be found on https://mbg.au.dk/en/news-and-events/vacancies/job/postdoc-position-in-neurobiology

Kind regards,
Gilles Vanwalleghem
Assistant Professor in Neurobiology
Department of Molecular Biology and Genetics
Aarhus University
Denmark

Ph.D. positions in Reinforcement Learning at TU Darmstadt
The LiteRL group, led by Dr. Carlo D'Eramo, funded by Hessian.AI, and located at TU Darmstadt, is seeking 2 Ph.D. students with a great interest in the highly interdisciplinary field of Reinforcement Learning. The LiteRL group will research lightweight methods for (deep) Reinforcement Learning to enhance autonomy and adaptation of agents.

All students with a passion for #AI and #MachineLearning are strongly encouraged to apply.

Complete job post at https://bit.ly/3lMVgP1

For any questions, drop me an e-mail!

Cheers!

Postdoc position social networks/loneliness in early adulthood
We are now inviting applications for a postdoctoral position at the Center for Social and Affective Neuroscience (CSAN), Linköping University, Sweden. The successful applicant will be mainly working on a project relating to social networks and loneliness in late adolescence/early adulthood. Specifically, the project will investigate social adjustments occurring when transitioning from a high school to a university. The project will focus on the general population and utilise multiple different data collection methods including ecological momentary assessment, fMRI and fEMG.

The applicant doesn’t need to be an expert in all of these methods, but they should preferably have experience in at least one of the above and be willing to learn the other ones. Strong statistical skills and experience in data analysis using R, Python, or Matlab are desirable. The successful candidate will have the ability to adapt the focus of the project to suit their own interests.

Duration: 2 years (salaried position)
Starting date: as soon as possible
Application deadline: January 3, 2022
Working language: English
Location: The Embodied Brain Lab (https://liu.se/en/research/csan/labs/morrison-lab), located in the Center for Social and Affective Neuroscience (https://liu.se/en/research/csan) at Linköping University, Linköping, Sweden

The full job ad, including instructions on how to apply, is available at https://liu.se/en/work-at-liu/vacancies?rmpage=job&rmjob=17644&rmlang=UK

Interested candidates can also contact India Morrison ([email protected]) or Juulia Suvilehto ([email protected]) for more information.

PhD and postdoctoral positions at LTSI INSERM Université de Rennes 1 in Virtual Reality, Surgical Training and Machine learning
Apply to a research project on "New digital forms for medical and surgical teaching"

The AIR project from the University of Rennes 1, in collaboration with University of Rennes 2, Inria, INSA and industrial IT companies, is one of the few national funded research projects to study new digital forms for teaching. Specifically, the AIR project aims to develop innovative operational solutions to increase and enrich pedagogical interactions through digital means. Within this project, the MediCIS/LTSI team aims 1) to develop innovative virtual reality based simulators to help learning non-technical medical and surgical skills, 2) to study data driven approaches for quantitative and objective assessment of skills based on machine learning and multimodal sensors, and 3) to promote the usage of and evaluate the developed systems and tools in medical contexts within the simulation center of the university and the collaborating medical simulation and training centers.

For this project, we are looking for one postdoc or research engineer and one PhD student in the area of virtual reality and artificial intelligence in medical and surgical training. The project will last three years. The MediCIS/LTSI lab is located within the medical university and is composed of researchers both from engineering and medicine working together on societal high value projects, in a context of responsible research, aware of social, environmental and ethical impacts.

Please contact [email protected] and [email protected] for more information (including CV and letter of motivation)

Pierre JANNIN
https://medicis.univ-rennes1.fr/
https://www.ltsi.univ-rennes1.fr/

LTSI, Inserm UMR 1099 - Université de Rennes 1
Equipe MediCIS
Faculté de Médecine 2, Avenue du Pr. Léon Bernard
35043 Rennes Cedex, France

Ph: +33 2 23 23 45 88
Fx: +33 2 23 23 69 17

Research Associate (Postdoc) position in autonomous driving, explainable AI, natural language processing

The successful candidate will join a team of interdisciplinary informatics researchers (AI planning and prediction, natural language processing, human cognitive modelling) in the School of Informatics, University of Edinburgh.

The goal of this project is to develop a system which enables human passengers to ask autonomous vehicles to explain their decisions (e.g. "Car, why did you change lanes just now? Why did you enter the junction while that other car was approaching?"). The project will build on the Interpretable Goal-based Prediction and Planning (IGP2) system published at ICRA'21 (see https://www.five.ai/igp2 for paper and videos) and develop new reasoning/explanation/NLP modules.

This position can start immediately and will have a duration of 1 year from the start of the position. International candidates are eligible. We are aiming to get additional funding to extend the position beyond 1 year.

For further details and how to apply, see here: https://elxw.fa.em3.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/job/2860/?utm_medium=jobshare

Application deadline: 5pm (UK time) on 10 January 2022

Enquiries about this position can be sent to Dr. Stefano Albrecht (https://agents.inf.ed.ac.uk/stefano-albrecht/).
--
Dr. Stefano V. Albrecht
Assistant Professor, School of Informatics, University of Edinburgh
Head of Autonomous Agents Research Group (https://agents.inf.ed.ac.uk)
Royal Society Industry Fellow, Five AI (https://www.five.ai)
Twitter: @UoE_Agents
The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th’ ann an Oilthigh Dhùn Èideann, clàraichte an Alba, àireamh clàraidh SC005336.

UK postdoc+phd opportunities in Trustworthy Machine Learning / Safe+Ethical AI at Cambridge and the Turing Institute
Come and join us!



Cambridge postdoc in trustworthy ML. Join the machine learning group at the University of Cambridge in the UK to work on Trustworthy Machine Learning, with a focus on Fairness, Interpretability or Robustness. We’re building foundational technical theory and methods, and working with partners in specific application settings in domains including healthcare and criminal justice.
Apply by 31 Dec https://www.jobs.cam.ac.uk/job/32684/



Turing postdocs in trustworthy, scalable, safe and ethical AI (RA or SRA level). Apply by Jan 3 https://cezanneondemand.intervieweb.it/turing/jobs/research_associatesenior_research_associate_for_safe__ethical_ai_18296/en/


Cambridge PhD. Although we’re past the cutoff date for some funding, it is still possible to apply, especially if you’re a strong candidate interested in scalable, trustworthy ML! https://mlg.eng.cam.ac.uk/?page_id=659


One area of interest is trying to ensure good performance not only of the AI system, but human-machine teams. We are always looking to connect with collaborators and stakeholders broadly. Please be in touch if interested.



Best wishes,

Adrian

--------------------------------------------------

Adrian Weller

https://mlg.eng.cam.ac.uk/adrian/

POST-DOC RESEARCHER in unsupervised statistical learning (M/F)
The offer is also available here : https://bit.ly/3s1fB6X
How to apply : https://bit.ly/3s1fB6X
Available in Paris (February 2022), France, 18 months

In general, multiview unsupervised learning provides superior results to single view and/or modality learning. These data are often heterogeneous and show significant divergence. Beyond multi-view learning, algorithms have recently been proposed to augment the properties of existing scalable clustering algorithms:

-Co-clustering, clustering individuals AND the variables used to describe them;
Probabilistic Clustering;
-Multi-clustering, aiming at performing a multi-view clustering while refining the membership of the variables to the various views;
-Topological Clustering, aiming at learning the clusters while organizing them on a low-dimensional map;
-Cell-based clustering, where the data atom is not necessarily a scalar but can be extended to a more complex structure;
-Transfer Clustering, where the result of a Clustering can be used to speed up and reduce the data requirement of a subsequent Clustering.

Although relevant and interesting separately, the properties of the above-mentioned algorithms would benefit from being combined into a general multi-view algorithm in order to take advantage of the most complete and explicit results possible with less effort.

The objective of this research project is to propose a general algorithm that combines as many of the properties mentioned above as possible, in order to limit the effort required for one person to perform reliable, topological Multi-Co-clustering with rich and explicit results (with high added value for this person) on very different datasets with multiple views / representations.
In view of the current state of the art in scalable co-clustering, we propose to address the fundamental dimension along two main axes: the first one aims at clustering the properties of cell-based probabilistic topological multi-view multi-clustering on multi-representation data, with the support of work recently done in collaboration with the LIPN; the second one aims at addressing the problem of transfer learning in the multi-view context.

**Activities

-Participate in research projects, within LIPN and in collaboration with the start-up HephIA, at the national and international levels, and in associated publications.
-Guide the choice of relevant algorithms and tools according to the problem at hand.
-Design algorithms for scalable co-clustering and visual restitution of results following the standards of the start-up HephIA.

**Skills

PhD in statistical learning or computer science (data science).
Strong background in statistics (mixture model) and computer science.
Programming skills in Python, Java/Scala
Experience with Git, Docker, Cloud environments, distributed computing on clusters
Experience in software engineering
Ability to synthesize.
Creativity, strength of proposal.

**Work Context

The post-doc researcher will join the A3 team: Artificial Learning & Applications (A3) of LIPN. The A3 team deals with problems related to machine learning and covers a broad scope of issues, including supervised and unsupervised learning and reinforcement learning. Its research is based on a variety of applications in the field of pattern recognition and data mining. The A3 team develops fundamental research while intensifying its cooperation with large organizations and industry.

This recruitment is part of the AMIES funding in collaboration with the start-up HephIA (https://hephia.com/).

Best regards
Mustapha Lebbah
------------------------------------------------------------------
Université Sorbonne Paris Nord,
Laboratoire d'Informatique de Paris-Nord (LIPN),
CNRS(UMR 7030),
99, av. J-B Clément
F-93430, Villetaneuse, France.
Tel: +331 49 40 38 94
Fax: +331 48 26 07 12
https://www-lipn.univ-paris13.fr/~lebbah

Two post-doctoral research associate positions at The Alan Turing Institute: Early Detection of Neurodegenerative Disease

The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. The Institute is named in honour of the scientist Alan Turing and its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better.

Position
The Alan Turing Institute has been awarded a grant by Alzheimer’s Research UK (ARUK) to lead the Analytics Hub for the EDoN initiative.

Early Detection of Neurodegenerative diseases (EDoN) is the largest initiative in the world that will collect, share and analyse clinical and digital health data to detect diseases like Alzheimer’s. Ultimately, this approach would be used by doctors to give an earlier and much more accurate diagnosis of dementia diseases.

The Alan Turing Institute is leading on the EDoN Analytics Hub which is tasked with designing and performing the analyses that will allow EDoN to make sense of the data collected in the project. The Analytics Hub is composed of data scientists and is responsible for developing, validating and refining machine learning ‘fingerprint’ models that can detect the diseases that cause dementia at their earliest stage.

The Health and Medical Sciences programme at the Turing delivers research into the theory and methods of AI, statistics, and data analytics underpinning medical and health applications that will enable scientists to do better science, without compromising respect for privacy and patient trust. The Analytics Hub is led by PI, Professor Richard Everson, and is recruiting two Senior Research Associate/Research Associates to support the data analytics and modelling.

Both roles are offed on a fixed term basis for 24 months. The annual salary is £37,000-£42,000 plus excellent benefits, including flexible working and family friendly policies, https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits

Please see full advertisement, job description and links to application form.



ROLE PURPOSE

The Research Associate will work closely with PI Professor Richard Everson and the Analytics Hub to deliver the data analytics and modelling aspects of the Analytics Hub. The post-holder will explore existing and develop novel machine learning methods to model and analyse retrospective and prospective data collected by the EDoN project and held in the Turing Secure Research Environment.

This role represents an outstanding opportunity to influence the direction of data intensive research to improve millions of people’s lives. You will develop novel methods to, for example, reduce misclassification of individuals due to co-morbidities, accurately predict particular disease subtypes, detect and model cognitive decline, combine multi-modal datasets. Initial work will be on retrospective data, but we will rapidly move to novel forms of data collected on low-burden digital platforms, such as smart phones and wearable technologies. Particular attention will be paid to issues around interpretability and reproducible research. You will produce breakthrough research in machine learning and data science for the early detection of neurodegenerative disease, publishing in top-rated journals and conferences.

DUTIES AND AREAS OF RESPONSIBILITY

Design and implement cutting edge statistical and machine learning methods to detect cognitive decline and dementia-causing diseases. Demonstrate internally across the EDoN consortia and the broader health data science communities, how data science and AI methods can provide predictive modelling to help clinicians in the detection of dementia.
Compare the power of cognitive, neuroimaging and digital markers in retrospective and prospective cohorts to accurately detect dementia.
Determine the integrity of digital markers and estimating the scale of data collection that will be necessary for the EDoN project’s overarching vision of detecting diseases like Alzheimer’s years before the symptoms of dementia start.
Analyse initial prospective data from the Predictors of COgnitive DECline in attenders of memory clinic (CODEC) study based at the Essex Neurocognitive Clinic along with other pilot data to determine the integrity of digital markers and estimating the scale of data collection that will be necessary.


Requirements
Essential

A PhD (or equivalent experience and/or qualifications) in a relevant area, which will include Statistics, Mathematics, Engineering, Computer Science, or related discipline.
Strong background in one or more of the following areas: Bayesian inference, ensemble models, multivariate time-series analysis, medical image analysis.
Experience managing, structuring and analysing research data.
An understanding of the importance of good practices for producing reliable software and reproducible analyses (e.g., version control, issue tracking, automated testing, package management, literate analysis tools such as Jupyter and Rmarkdown.
Excellent written and verbal communication skills, including experience in the visual representation of quantitative data, the ability to write for publication, present research proposals and results, and represent the research group at meetings.
Ability to carry out original research and to produce published research papers.
Please see the Job description for a full breakdown of the duties and responsibilities as well as the person specification. https://cezanneondemand.intervieweb.it/turing/jobs/research_associate__edon_initiative_18886/en/

PhD fellowship at Institut Curie (Causal Inference and Machine Learning)

Marcel Ribeiro Dantas <[email protected]>
Attachments
Sat, Dec 18, 6:11 PM (4 days ago)
to Machine Unsubscribe

Dear all,

I would like to share with you this fellowship to pursue a PhD in Causal Inference and Machine Learning at Institut Curie in Paris, France.

More details can be found in the PDF attached to this email.

Best regards,




Marcel Ribeiro-Dantas Early Stage Researcher at Institut Curie
Isambert Team | UMR168

PhD Student at Sorbonne Université
MSc in Bioinformatics (UFRN)
Graduate certificate in Big Data (UFRN)
Computer and Automation Engineer (UFRN)
w: https://mribeirodantas.me/
e: [email protected]
a: 11 rue Pierre et Marie Curie, 75005 Paris, France.

Postdoc position in Robotics at Warwick
University

The Department of Physics seeks to appoint an ambitious Research Fellow to
join the Ultrafast and Terahertz Photonics group at the University of Warwick.
The position is available as soon as possible for up to three years in
duration. Join our team to make a difference to the fight against cancer.

You will join the EPSRC-funded £8M project 'Terabotics' led by Professor Emma
MacPherson at the University of Warwick. You will work closely with the
Robotics Team led by Professor Pietro Valdastri at the University of Leeds and
also collaborate with clinicians at the University Hospital Coventry &
Warwickshire. Your research goals will be related to developing robotics for
applying THz imaging and spectroscopy techniques to detection of skin cancer
and other skin conditions. Particular focus will be on integrating THz image
approaches with the KUKA surgical robot, and speeding up and improving the
accuracy of terahertz data acquisition.

You will be an excellent communicator capable of working effectively both
independently and as part of a research team. You will possess excellent
planning and time management skills to ensure your research objectives are
achieved effectively.

If you have not yet been awarded your PhD but are near submission or have
recently submitted your PhD, any offers of employment will be made as Research
Assistant on level 5 of the University grade structure (£30,497. Upon
successful award of your PhD and evidence of this fact, you will be promoted
to Research Fellow on the first point of level 6 of the University grade
structure (£31,406 pa).

For more information about the role, please click
here<https://urldefense.com/v3/__https://warwick.ac.uk/fac/sci/physics/research/condensedmatt/ultrafastphotonics/emmasthzgroup/terabotics/vacancies/__;!!LIr3w8kk_Xxm!82VDh4kchPL4CjP90jc-qvrJhI1ynt6fV3A_I4fnxdbigKfOpAY_AKBiR02Dg4eaaOSPyL4G$
>. Please direct all informal inquiries to Dr Emma MacPherson:
[email protected]<mailto:[email protected]>.


Kind Regards,

Taherah

Taherah Nureen
Project Coordinator
Dept of Physics
University of Warwick
Coventry CV4 7AL

Four funded PhD positions at ISR -
University of Coimbra

The Institute of Systems and Robotics at University of Coimbra has opened a
call for 4 Ph.D. positions on the following topics:

Ref. BD4/2021_topic_1 - Cooperative multimodal perception in outdoor mobile
robot teams – a deep learning approach

Ref. BD4/2021_topic_2 - Integration of 6D object pose estimation in a Dynamic
P300-based brain-computer interface (BCI)

Ref. BD4/2021_topic_3 - Socio-Spatial Assistance for Human-Robot Interaction

Ref. BD4/2021_topic_4 - Self-powered autonomous biomonitoring wearable systems

The description of the research to be pursued in each of the four research
topics are included in the footer of this message.

§ Application deadline
December 31, 2021, 23:00 (WET)

§ Application submission
The applications must be sent by email to [ mailto:[email protected] |
[email protected] ] **specifying in the subject the reference of one of the 4
topics defined in the footer of this message. The application must include the
following documentation: CV, habilitation certificate including the final
scores obtained in the undergraduate subjects and a motivation letter.
Recommendation letters are valued but not mandatory.

Fully Funded PhD - ICube, Strasbourg, France: Domain invariant interpretable representation learning for satellite image time-series
A fully funded PhD position is open at the University of Strasbourg (ICube). The position will be jointly funded by the French National Centre for Space Studies (CNES) and the Chair SDIA. 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 to develop novel deep learning approaches to domain invariant representation learning for satellite image time-series (SITS).

Domain invariant interpretable representation learning for satellite image time-series
The goal of the project is to develop models for learning domain invariant representations using deep learning for the analysis of satellite image time-series.

It is difficult and expensive to annotate the huge amount of data generated by satellites, but this is needed for the success of deep learning algorithms. To overcome this, transfer learning and domain adaptation techniques will be developed to exploit unlabelled data. These techniques allow an algorithm’s performance to be improved with minimal (or potentially no) additional annotation, lowering the cost of deployment.

The successful candidate will have (or will soon obtain) an MSc in Computer Science or related subject. Experience with deep learning is required and experience with time series and/or remote sensing is a bonus.

Send a letter of motivation and your CV to Thomas Lampert and Gisèle Burgart ([email protected] and [email protected] - !remove the numbers!) with the subject beginning with [CNES PhD].

The application deadline is 15/3/2022 and the starting date will be September 2022 (or soon after).

Detailed Description: https://drive.google.com/file/d/1W92enhzhKLJ0_IjD4pSSMYHw-y6SxQdj/view?usp=sharing

Postdoc Position at Princeton University (PI: Dr. Erik Nook)
Hello,

Please see below for a postdoc job ad in my lab starting next summer. I would appreciate your assistance in spreading the word!

Many thanks,
Erik Nook

Application for Postdoctoral Research Associate

The Department of Psychology at Princeton University invites applications for a Postdoctoral Research Associate or more senior position. Applicants should have a PhD degree (or expect to receive a PhD degree by September 1, 2022) in Psychology or allied fields (e.g., Neuroscience, Education, Sociology) with an interest in conducting research on human emotion.

The Postdoctoral Research Associate will work with Dr. Erik Nook in his lab set to launch July 2022. The lab's research will integrate behavioral, developmental, psycholinguistic, and neuroscientific approaches to advance both basic and translational understanding of human emotion. Responsibilities will include working with large datasets, collecting new data (potentially using behavioral, developmental, online, web scraping, and/or fMRI methods), processing data (e.g., preprocessing linguistic and/or fMRI data), running advanced statistical models, visualizing data and results, writing manuscripts, presenting research, and mentoring undergraduate and graduate researchers. Expertise in any or all of these skills is not required. However, familiarity with some of these approaches is preferred, as specific research projects will emerge through collaborative conversations that extend both the Postdoctoral Associate and Dr. Nook's programs of research. To learn more about potential areas of synergy, please refer to the research questions described on Dr. Nook's website (https://scholar.harvard.edu/eriknook).

The position is offered for 1 year, with the possibility of renewal, contingent upon funding and satisfactory performance. In addition to the aforementioned project, the appointee will have opportunities to develop additional projects with members of Dr. Nook's lab. The position will start on or around July 2022. This position is subject to the University's background check policy. Salary will be in accordance with NIH guidelines.

Applicants must apply online at https://www.princeton.edu/acad-positions/position/23781 and submit the following documents: (i) a cover letter, (ii) a C.V., (iii) a research statement, (iv) 1-2 research papers, and (v) names of two referees who can provide letters upon request. The cover letter should focus on the applicant's academic and technical training (i.e., research and academic training so far, current technical skills, postdoctoral training goals, and how the current postdoctoral position will allow applicants to reach these goals). The research statement should focus on the applicant's research (i.e., the core research questions within the applicant's scholarly focus, a synthesis of projects completed so far, and potential future directions of research). Applicants are welcome to include other information in these documents if they deem it relevant. Submissions will be reviewed on a rolling basis, with priority given to submissions received before February 1st, 2022.

post doc opening in ultrasound imaging at the Social Brain Lab
Dear all,
the Social Brain Lab at the Netherlands Institute for Neuroscience (Amsterdam, NL) is opening a post-doc position in ultrasound imaging in rodents to investigate the neural bases of empathy. The position is mainly about improving the image sequences and developing data analysis pipelines. A PhD student already working on the project will be acquiring the data. The post-doc will therefore not need to have animal experience, but rather computational and analytical skills.

Attached you will find the advertisement with the link to more information.
Deadline January 8th!

robotics-worldwide digest Thu, 16 Dec 2021

Table of contents:

* 1 - [robotics-worldwide] [jobs] Fully Funded PhD in Smart cyber-physical
systems for assistive technology at home for the elderly - University of
Bath - Uriel Martinez Hernandez <[email protected]>
* 2 - [robotics-worldwide] [Meetings] IEEE ARM 2022 , Special Session:
Combining the advanced intelligent approaches with medical systems: the
state of the art and challenges - lics <[email protected]>
* 3 - [robotics-worldwide] [meetings] The 17th International Conference on
Intelligent Autonomous Systems (IAS-17): Call for Participation - Ivan
Petrović <[email protected]>

----------------------------------------------------------------------

Message-ID:
<LO2P265MB3689DDC513B30E6ADD3BD5AA8A759@LO2P265MB3689.GBRP265.PROD.OUTLOOK.COM>
Date: Tue, 14 Dec 2021 22:18:38 +0000
From: Uriel Martinez Hernandez <[email protected]>
Subject: [robotics-worldwide] [jobs] Fully Funded PhD in Smart cyber-physical
systems for assistive technology at home for the elderly - University of Bath

Fully Funded PhD studentship in Smart cyber-physical systems for assistive
technology at home for the elderly

Centre for Autonomous Robotics (CENTAUR) and the Department of Electronic and
Electrical Engineering, University of Bath

Application deadline: 23rd January 2022

Description:
https://urldefense.com/v3/__https://www.findaphd.com/phds/project/smart-cyber-physical-systems-for-assistive-technology-at-home-for-the-elderly/?p139285__;!!LIr3w8kk_Xxm!88YjZnh-PUK06MCe1CKR9s4rYpjs9_X5GvctHJapyR1XzZv_1zAf5kjCPuOdStD7sqZ6Hje2$
How to apply:
https://urldefense.com/v3/__https://www.bath.ac.uk/guides/how-to-apply-for-doctoral-study/__;!!LIr3w8kk_Xxm!88YjZnh-PUK06MCe1CKR9s4rYpjs9_X5GvctHJapyR1XzZv_1zAf5kjCPuOdStD7smyDTk8a$

Start date: October 2022

-------

About the Project

Cyber-physical systems (CPS) is the emerging systems of intelligence that
seeks to exploit the combination of sensor elements, embedded and wearable
sensors systems, computing, artificial intelligence, robotics, networking and
actuation to monitor and control physical systems. These features can make CPS
capable of autonomously functioning based on the monitoring and interaction
with their physical surrounding. This means that CPS have great potential for
the development of intelligent devices capable of safely, reliably and
efficiently assisting individual at home and to perform activities of daily
living.

This project will investigate and develop novel and robust CPS architectures
for smart, safe, efficient, and timely assistive technology at home for the
elderly. The aspects that will be investigated for these CPS include the
following:

Optimal sensing modalities located at home and worn by the user.
Machine learning methods for activity recognition using multimodal data.
Wearable and comfortable sensor arrays for biometric sleep detection and fall
detection.
Smart control of appliances for safe and optimised usage at home by the
elderly.
Real-time data systems for monitoring, IoT and fast response in emergency
events.

The outcomes from this research project will contribute to deliver smart
healthcare systems that allow the elderly to stay healthy and independent at
home, make the elderly feeling safe at home and recovering their quality of
life. This work will contribute to the development of smarter control system
at home based on the current state of the user. Furthermore, this research
will also contribute and open research opportunities to transform how care and
assistance is delivered currently.

The PhD student will have access to the facilities of the Multimodal
Interaction and Robotic Active Perception lab (Inte-R-action), the Centre for
Autonomous Robotics (CENTAUR) and the Centre for Bioelectronics, Biosensors
and Biodevices (C3Bio).


Enquiries and Applications

Informal enquiries are welcomed and should be directed to Dr Uriel Martinez-
Hernandez - [email protected]
Formal applications should be made via the University of Bath's online
application form for a PhD in Electronic and Electrical Engineering.
When completing the form, please identify your application as being for the
URSA studentship competition in Section 3 Finance (question 2) and quote the
project title and lead supervisor's name in the 'Your research interests'
section.


Funding Eligibility

To be eligible for funding, you must qualify as a Home student. The
eligibility criteria for Home fee status are detailed and too complex to be
summarised here in full; however, as a general guide, the following applicants
will normally qualify subject to meeting residency requirements: UK nationals
(living in the UK or EEA/Switzerland), Irish nationals (living in the UK or
EEA/Switzerland), those with Indefinite Leave to Remain and EU nationals with
pre-settled or settled status in the UK under the EU Settlement Scheme). This
is not intended to be an exhaustive list.


Funding Notes

Candidates may be considered for an URSA studentship, tenable for 3.5 years.
Funding covers tuition fees at the Home rate, a £1000 per annum training
support fee, and a stipend at the UKRI rate (£15,609 p/a in 2021/22).
An URSA studentship only covers tuition fees at the Home tuition fee rate, and
so students eligible for Overseas tuition fee status are not eligible to
apply. Exceptional Overseas students (e.g. with a UK Masters Distinction or
international equivalent) who are interested in the project should contact the
intended supervisor in the first instance, to discuss the possibility of
applying for additional funding.


Do not hesitate to contact me if you have any further questions.

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Uriel Martinez-Hernandez
Lecturer (Assistant Professor) in Robotics
Department of Electronic & Electrical Engineering
Faculty of Engineering and Design
University of Bath

Fully funded PhD positions (4 years) in Machine Learning at ML-Labs, Dublin, Ireland
We are delighted to announce funded PhD positions with ML-Labs (SFI Centre for Research Training in Machine Learning) in Dublin, Ireland.
The positions start in September 2022.

The PhD programme is designed to take on a cohort of students each year (20-30 positions) and has a strong focus on
developing both technical and transferable skills during the graduate programme.
It also has a strong connection to Ireland-based industry and an industry internship is a mandatory part of the programme.

For more information, an ML-Labs at-a-glance flyer is attached.
To check eligibility and to apply please go to: https://ml-labs.ucd.ie

Deadline to apply: February 4, 2022.
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About ML-Labs: SFI Centre for Research Training in Machine Learning
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The SFI Centre for Research Training in Machine Learning is an internationally
connected and globally recognised postgraduate research training centre specialising in
Machine Learning and designed to address the urgent industry demand for ML talent.

For the first time the promise of machine learning – software that can automatically
improve with experience – is becoming a commercial reality due to a combination of
the availability of big data, ever increasing computational power, and a clear industry demand.
The result has been an explosion of machine learning applications,
from advertising to healthcare, and an unprecedented demand for machine learning graduates,
both globally and in Ireland. The centre is a significant contribution to this demand,
aiming to train 120 academically outstanding, industry-ready PhD graduates,
with an intake each year between 2019 to 2023. These graduates will be future leaders managing
the disruption that machine learning is causing across industry and society and will strengthen the reputation of Ireland
as a global hub for machine learning education, research, and application.

The centre is a collaboration between University College Dublin (UCD),
Dublin City University (DCU), and the Technological University Dublin (Tu Dublin)
and brings together a team of more than 50 academic supervisors working at the cutting-edge of machine learning
research and its application, as well as a group of 20 Ireland-based companies,
both multinational and SME, that have already partnered with the centre.