At a Glance
- Tasks: Join a cutting-edge team researching probabilistic machine learning and collaborate on innovative AI projects.
- Company: University of Manchester, a leader in AI research and innovation.
- Benefits: Competitive salary, access to world-class resources, and opportunities for professional growth.
- Other info: Exciting collaborations across various fields including medicine and synthetic biology.
- Why this job: Make a real impact in AI while working with top researchers in a dynamic environment.
- Qualifications: Experience in machine learning and a passion for research in AI.
The predicted salary is between 36000 - 60000 £ per year.
Still some days to apply for Postdoc and Research Fellow positions in probabilistic machine learning at the University of Manchester, UK
Sep 20, 2022
The Manchester Centre for AI Fundamentals has positions for Postdocs and Research Fellows. The application deadline is September 30.
We have hired a number of new researchers and faculty members, and the next recruitment round is ongoing.
I am hiring researchers for my team working on probabilistic machine learning. Keywords include: Bayesian inference, reinforcement learning, inverse reinforcement learning, automatic experimental design, multi-agent learning, Bayesian deep learning, amortized inference, human-in-the-loop learning, user modeling, collaborative AI, privacy-preserving learning, and likelihood-free inference. Researchers work on different but related subsets of these topics. The work is funded by UKRI Turing AI World-Leading Researcher Fellowship programme, focusing on "Steering AI in Experimental Design and Decision-Making".
The team is based in the new Manchester Centre for AI Fundamentals, which collaborates with the ELLIS Unit Manchester and the Alan Turing Institute. Besides AI and Machine Learning, we collaborate with teams in personalized medicine (especially cancer and remote medicine), synthetic biology, digital twins, and more, in both academia and industry.
Additionally, the university is hiring a Full Professor of Artificial Intelligence in Biology, Medicine, and Health (link) and will soon open another faculty position in Machine Learning. We are also open to proposals for excellent PhD candidates and Research Software Engineers.
This is a great time to join the University of Manchester as it significantly boosts its activities in Machine Learning!
#J-18808-LjbffrStill some days to apply for Postdoc and Research Fellow positions in probabilistic machine lea[...] in Manchester employer: The International Society for Bayesian Analysis
The University of Manchester is an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration in the field of probabilistic machine learning. With access to cutting-edge research facilities and partnerships with leading institutions like the Alan Turing Institute, employees benefit from extensive growth opportunities and the chance to contribute to groundbreaking projects in AI and healthcare. Join us to be part of a dynamic team dedicated to advancing knowledge and making a meaningful impact in the world.
Contact Details:
The International Society for Bayesian Analysis Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Still some days to apply for Postdoc and Research Fellow positions in probabilistic machine lea[...] in Manchester
✨Tip Number 1
Network like a pro! Reach out to current researchers or faculty members at the University of Manchester. A friendly chat can give us insights into the team culture and might even lead to a referral.
✨Tip Number 2
Showcase your skills! Prepare a portfolio or a presentation that highlights your work in probabilistic machine learning. This will help us stand out during interviews and demonstrate our expertise.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or colleagues. This will help us refine our answers and boost our confidence before the real deal.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can keep track of our application status easily.
We think you need these skills to ace Still some days to apply for Postdoc and Research Fellow positions in probabilistic machine lea[...] in Manchester
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your application for the specific Postdoc or Research Fellow position. Highlight your experience with keywords from the job description, like Bayesian inference and reinforcement learning, to show us you’re a perfect fit!
Showcase Your Research:Don’t just list your past work; tell us how it relates to the projects we’re working on at the Manchester Centre for AI Fundamentals. We want to see your passion for probabilistic machine learning shine through!
Keep It Clear and Concise:While we love detail, make sure your application is easy to read. Use clear headings and bullet points where necessary. This helps us quickly grasp your qualifications and makes a great first impression!
Apply Through Our Website:We encourage you to submit your application through our official website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at The International Society for Bayesian Analysis
✨Know Your Stuff
Make sure you brush up on the key topics mentioned in the job description, like Bayesian inference and reinforcement learning. Familiarise yourself with recent advancements in these areas, as well as any relevant projects you've worked on that showcase your expertise.
✨Prepare Thoughtful Questions
Interviews are a two-way street! Prepare insightful questions about the research team's current projects or future directions. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
✨Showcase Collaboration Skills
Since the role involves collaboration with various teams, be ready to discuss your experience working in interdisciplinary settings. Share examples of how you've successfully collaborated with others, especially in AI or machine learning contexts.
✨Practice Problem-Solving
You might be asked to solve a problem or case study during the interview. Brush up on your problem-solving skills related to probabilistic machine learning. Practising with real-world scenarios can help you articulate your thought process clearly.
