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Post-doctoral positions in Information Theory and related areas - U. of Cambridge
We invite applicants for Post-Doctoral Research Associate positions to work in information theory, quantum information theory, and statistical inference, funded by the EPSRC Hub on Information Theory for Distributed Artificial Intelligence.

We invite applicants for Post-Doctoral Research Associate positions to work in information theory, quantum information theory, and statistical inference. These positions 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, Durham University, and Imperial College London. The successful candidates will be based in Cambridge, hosted by Nilanjana Datta (DAMTP), Ioannis Kontoyiannis, and/or Po-Ling Loh (DPMMS), and co-supervised by one of the following collaborators at partner institutions: Ayalvadi Ganesh, Sidharth Jaggi, Oliver Johnson (Bristol), Neil Walton, Thiru Vasantam (Durham), Deniz Gunduz, or Seyed Mohsen Moosavi-Dezfooli (Imperial).

DEADLINE: Closing date for applications is Tuesday 12 March 2024. Interviews will take place as soon as possible following the closing date.

APPLICATION FORM: https://www.jobs.ac.uk/job/DFX388/post-doctoral-research-associate-x-3-fixed-term

This is an exceptional opportunity to conduct ambitious research at the forefront of mathematics, statistics, (quantum) 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.

Duties include developing and conducting individual and collaborative research projects as part of the overall work of the INFORMED-AI programme. The successful candidate must be able to communicate material of a technical nature and be able to build internal and external contacts. The successful candidate may also be asked to assist in the supervision of student projects, provide instruction, and plan/deliver seminars relating to the research areas of INFORMED-AI.

Applicants must have (or 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.

Start date: 1 October 2024 or by mutual agreement. 

Fixed-term: The funds for this post are available for 3 years in the first instance.

You will need to upload a full curriculum vitae and research statement (the latter should not exceed three pages). The contact details of two referees will be required; please ensure that your referees are aware that they may be contacted by the Mathematics HR Office Administrator to request that they upload a reference for you to our Web Recruitment System; please encourage them to do so promptly.

Informal inquiries can be directed to  [email protected].

Please quote reference LF40384 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.