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- Tasks: Conduct groundbreaking research in information theory and statistics, focusing on distributed testing and estimation.
- Company: Join a collaborative team from top UK universities, including Cambridge and Bristol.
- Benefits: Generous funding for conferences, travel, training, and career development.
- Why this job: Make a real impact in AI research at the forefront of mathematics and machine learning.
- Qualifications: PhD in mathematics, statistics, engineering, or computer science; experience in relevant fields preferred.
- Other info: Engage with academic communities and industrial partners while enjoying a dynamic research environment.
The predicted salary is between 36000 - 60000 £ per year.
Overview
We would like to advertise one position for a Post-Doctoral Research Associate to work in topics at the intersection of information theory and statistics. This position will be funded by the EPSRC AI Hub on Information Theory for Distributed Artificial Intelligence (INFORMED-AI). INFORMED-AI is a joint programme run by the University of Bristol, the University of Cambridge, the University of Durham, and Imperial College London. The successful candidate will be based in Cambridge, primarily hosted by Varun Jog and co-supervised by Po-Ling Loh (Cambridge) and Sidharth Jaggi (Bristol).
The PDRA\’s main project will involve investigating several theoretical questions concerning distributed testing and estimation, particularly in streaming settings where agents have limited memory. They will study tradeoffs between memory, accuracy, and sample complexity of fundamental questions in hypothesis testing. In addition, the PDRA may be responsible for developing and conducting collaborative research projects as part of the overall work of the INFORMED-AI programme.
This is an exceptional opportunity to conduct ambitious research at the forefront of mathematics, statistics, information theory, and machine learning. There are generous funds available for conference attendance, travel, computer equipment, training, and career development.
The vision and ambition of INFORMED-AI is to develop the theoretical foundations of artificial intelligence, specifically in the area of collective intelligence, addressing aims such as 1) trustworthy collective intelligence, 2) connectivity and resilience, and 3) heterogeneous distributed artificial intelligence.
The four-university team which the successful candidate will join combines leading expertise in information theory, theoretical statistics, applied probability, optimization, robustness, privacy, machine learning, game theory, artificial intelligence, and robotics. Interaction with industrial partners will be encouraged. The ideal candidate will also help serve as a bridge between the information theory groups at Cambridge and Bristol. In particular, while based in Cambridge, the PDRA would be expected to make regular visits to Bristol and engage in the academic communities at both Cambridge and Bristol, participating regularly in IT/statistics/ML seminars, attending and presenting in reading groups, and helping co-supervise PhD students.
Responsibilities and qualifications are described below under the relevant sections.
Responsibilities
Responsibilities include conducting research in information theory, statistics, and machine learning as they relate to distributed testing and estimation, particularly in streaming settings with limited memory. The PDRA may also develop and conduct collaborative research projects as part of the INFORMED-AI programme and engage with the four-university team and industrial partners as appropriate. Regular visits to Bristol and engagement with Cambridge and Bristol academic communities, seminars, reading groups, and co-supervising PhD students are expected.
Qualifications
Applicants must have (or be about to receive) a PhD degree in mathematics, statistics, engineering, or computer science. The ideal candidates will be experienced in one or more of the following areas: classical or quantum information theory, mathematical statistics, machine learning, and optimization.
Appointment details
Limit of tenure: 2 years, with possible extension as funds permit.
Start date: 1 July 2026 or by mutual agreement.
Application process
Click the \’Apply\’ button below to register an account with our recruitment system (if you have not already) and apply online.
Please indicate the contact details of two academic referees on the online application form and upload a full curriculum vitae and a research statement (not to exceed three pages). Please ensure that at least one of your referees is contactable at any time during the selection process and is made aware that they will be contacted by the Mathematics HR Administrator to request that they upload a reference for you to our Web Recruitment System, and please encourage them to do so promptly.
Closing date for applications is 1 December 2025.
Interviews will take place as soon as possible following the closing date.
If you have any questions about this vacancy or the application process, please contact LF47619@maths.cam.ac.uk.
Please quote reference LF47619 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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Postdoctoral Research Associate in Information Theory and Statistics (Fixed Term) employer: University of Cambridge
Contact Detail:
University of Cambridge Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Postdoctoral Research Associate in Information Theory and Statistics (Fixed Term)
✨Network Like a Pro
Get out there and connect with folks in your field! Attend seminars, workshops, and conferences related to information theory and statistics. Engaging with the academic community can lead to valuable opportunities and collaborations.
✨Show Off Your Research Skills
When you get the chance to chat with potential employers or collaborators, make sure to highlight your research experience. Discuss your projects, findings, and how they relate to distributed testing and estimation. This will show them you're not just a candidate, but a passionate researcher!
✨Tailor Your Approach
Before any interview or networking event, do your homework on the people you'll be meeting. Understand their work and how it connects to yours. This way, you can have meaningful conversations that demonstrate your interest and knowledge in the field.
✨Apply Through Our Website
Don't forget to apply through our website for the Postdoctoral Research Associate position! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Postdoctoral Research Associate in Information Theory and Statistics (Fixed Term)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in information theory, statistics, and machine learning. We want to see how your background aligns with the exciting research at INFORMED-AI, so don’t hold back on showcasing your skills!
Craft a Compelling Research Statement: Your research statement should not only outline your past work but also demonstrate your vision for future research. We’re looking for innovative ideas that fit within the scope of distributed testing and estimation, so let your creativity shine!
Choose Your Referees Wisely: Select referees who can speak to your academic prowess and research capabilities. It’s crucial that at least one referee is available during the selection process, so give them a heads-up to ensure they can provide a prompt reference.
Apply Through Our Website: Don’t forget to hit that 'Apply' button on our website! It’s the easiest way to submit your application and ensures it gets to the right people. We can’t wait to see what you bring to the table!
How to prepare for a job interview at University of Cambridge
✨Know Your Stuff
Make sure you brush up on your knowledge of information theory, statistics, and machine learning. Be prepared to discuss your research experience and how it relates to distributed testing and estimation. Familiarise yourself with the latest developments in these fields, especially those relevant to the INFORMED-AI programme.
✨Engage with the Team
Since you'll be working closely with experts from multiple universities, show genuine interest in their work. Research Varun Jog, Po-Ling Loh, and Sidharth Jaggi's contributions and think about how your skills can complement theirs. This will demonstrate your enthusiasm for collaboration and your ability to integrate into their academic community.
✨Prepare Thoughtful Questions
Interviews are a two-way street! Prepare insightful questions about the projects you'll be involved in, the team dynamics, and opportunities for professional development. This shows that you're not just interested in the position but also in how you can grow and contribute to the team.
✨Showcase Your Communication Skills
As a Postdoctoral Research Associate, you'll need to communicate complex ideas clearly. Practice explaining your research in simple terms and be ready to discuss how you would engage with PhD students and industrial partners. Strong communication skills will set you apart from other candidates.
