Welcome to Mathematics and Research!
This is your global hub for:

PhD & job opportunities in mathematics

Open-source learning resources

Math facts, memes, and tools

And everything in between!


Whether you're a student, researcher, or math fan—this space is for you.

Stay tuned, stay curious, and share with your peers.
Let’s grow the math community—together!
@mathandresearch

PhD-Level Job Opportunity: Assistant Lecturer in Statistics
Institution: University of Alberta (Canada)
Location: Edmonton, Alberta (Hybrid work option)
Start Date: July 1, 2025
Contract: 1–3 years (renewable, with potential for career position)
Deadline to Apply: June 4, 2025

Requirements:
• Master’s or PhD in Statistics or Mathematics
• Strong teaching experience and interest in undergraduate education

To Apply:
Submit a CV, cover letter, teaching profile, and 3 letters of reference.

Official Link:
https://apps.ualberta.ca/careers/posting/2328

Let your fellow mathematicians know—opportunities like this matter!
https://t.iss.one/+hR-zIN7PVAEzZTIy

#PhDJobs #MathJobs #Statistics #CanadaJobs #AcademicPositions
#Mathematics

@mathandresearch

Who is your academic advisor? Whose academic lineage are you part of?
Discover your mathematical ancestors with:

Math Genealogy Project – the ultimate academic family tree for mathematicians.

With this site, you can:
• Find out who supervised your PhD
• Trace your advisor’s advisor — and so on
• Explore your full academic lineage
• See how many students are part of your academic legacy

Just search your name (or any mathematician's), and you’ll uncover a fascinating academic history.

A must-visit for PhD students, researchers, and anyone interested in the roots of mathematical thought.

Check it out:
https://www.genealogy.math.ndsu.nodak.edu


Let your fellow mathematicians know about it.
https://t.iss.one/+hR-zIN7PVAEzZTIy

#MathGenealogy #AcademicLineage #MathematicsHistory #PhDNetwork
#Mathemtics
#Research

@mathandresearch

🎥 Feynman on Mathematicians vs. Physicists

If you’re into math and physics, you’ve got to watch this gem! Richard Feynman breaks down the key differences in how mathematicians and physicists think—super insightful and entertaining. Perfect for anyone curious about the two fields! 🔢⚙️

#Mathematics #Physics #Feynman #Research

Join us 👇👇👇
https://t.iss.one/mathandresearch

Here’s what you should do during your PhD if you want strong opportunities in industry (or outside academia):

1. Learn Python and R – they're the languages of data and analytics.


2. Take machine learning courses – even basic ML will set you apart.


3. Build a GitHub portfolio – show your skills, don’t just talk about them.


4. Network outside academia – connect with industry pros on LinkedIn, attend meetups, DM people. Build bridges.



🎯 Don’t wait until after your PhD to get ready. Start now—future you will thank you.

#PhDTips #BeyondAcademia #MathInIndustry #CareerAdvice
#Mathematics

Join us👇👇👇
https://t.iss.one/mathandresearch

BambooHR https://iuk.bamboohr.com/careers/37

W2 Professorship in Pure Mathematics — University of Bonn
https://www.uni-bonn.de/en/university/working-at-the-university/job-opportunities/vacancies-1/w2-professorship-in-pure-mathematics

Doctoral fellow — Ghent University https://www.ugent.be/en/work/scientific/doctoral-fellow-3

Applicants should hold the master's in Computer science, Bioinformatics or related fields.

Job Posting II-348/25: 6 positions - Research Assistant - 0.75 working time - salary grade E13 TV-L Berliner H... – Job Postings at Technische Universität Berlin
https://www.jobs.tu-berlin.de/en/job-postings/196875?filter%5Bfulltextsearch%5D=&filter%5Bworktype_tub%5D%5B%5D=wiss-dauer&filter%5Bworktype_tub%5D%5B%5D=wiss-mlehr&filter%5Bworktype_tub%5D%5B%5D=wiss-olehr&filter%5Bworktype_tub%5D%5B%5D=wiss-pdoc

Postdoc position: Computational methods for neurodegeneration research - VIB https://share.google/Y0TYFaWfGI3UUToel


https://t.iss.one/mathandresearch

In the empirical probability approach, the probabilities are based on observed data, not
on prior knowledge of a process. Surveys are often used to generate empirical probabilities.

Examples of this type of probability are the proportion of individuals in the Using Statistics
scenario who actually purchase big-screen televisions, the proportion of registered voters who
prefer a certain political candidate, and the proportion of students who have part-time jobs.

For example, if you take a survey of students, and 60% state that they have part-time jobs, then
there is a 0.60 probability that an individual student has a part-time job.


The third approach to probability, subjective probability, differs from the other two
approaches because subjective probability differs from person to person. For example, the
development team for a new product may assign a probability of 0.60 to the chance of success
for the product, while the president of the company may be less optimistic and assign a probability of 0.30. The assignment of subjective probabilities to various outcomes is usually based on a combination of an individual’s past experience, personal opinion, and analysis of a particular situation. Subjective probability is especially useful in making decisions in situations in
which you cannot use a priori probability or empirical probability

Check out this job at Khalifa University: https://www.linkedin.com/jobs/view/4299152588

For more news, join us https://t.iss.one/mathandresearch