Applications are invited for up to three Post-Doctoral Research Associates to work on information theory, decentralised decision-making, and engineering applications. The positions are funded by the EPSRC AI Hub on Information Theory for Distributed Artificial Intelligence (INFORMED-AI), a joint initiative between the Universities of Bristol, Cambridge and Durham, and Imperial College, London. The vision of the Hub is to develop the theoretical foundations of collective intelligence, including security and privacy, resilience and fault tolerance, and heterogeneity. 

Successful candidates will based in Bristol, supervised by Ayalvadi Ganesh, Sidharth Jaggi, Oliver Johnson or Jonathan Lawry, and co-supervised by a collaborator at a partner institution: Ioannis Kontoyiannis, Po-Ling Loh, Nilanjana Datta or Amanda Prorok (Cambridge), Neil Walton or Thiru Vasantam (Durham), or Deniz Gunduz, Yiannis Demeris or Seyed Moosavi-Dezfooli (Imperial). Funds for this post are available for up to 3 years in the first instance, with a generous allowance for training, conference travel and collaboration. 

This is an exciting opportunity to conduct ambitious research at the interface of information theory, statistical machine learning and applications as part of an interdisciplinary team. Successful candidates will be expected to contribute to activities across the hub, including research and publication, developing academic collaboration opportunities, and engaging in training and knowledge exchange.  

Duties of the research associate include

(i) developing and conducting individual and collaborative research projects as part of the overall work of the INFORMED-AI programme,

(ii) writing up research results in a form suitable for journals or conferences, and

(iii) presenting their work at seminars and conferences.

While teaching is not a required part of this role, there will be the option to undertake development opportunities in teaching or project supervision.

• Applicants should have a PhD degree in mathematics or a closely related discipline (or be working towards one), with expertise in probability, theoretical statistics, theoretical computer science or machine learning.
• Good oral and written communication skills are essential.
• We welcome applicants from all backgrounds.

The closing date for the application is 12th May. Interviews are likely to be held on or around the 13/14th of May 2024 and to be held online.

Please see the link below for more details. Please note, out of the three available posts one will be based in the School of Engineering Mathematics and Technology, Faculty of Engineering, and two in the School of Mathematics, Faculty of Science.

Link to the job advert here.