Research Fellow in Bio-Inspired Artificial Intelligence and Robotics Ref 10131

School/department: School of Engineering and Informatics
Hours: Full time. Requests for flexible working options will be considered (subject to business need).
The position involves teamwork and frequent interactions with team members as well as field work in Sussex and two visits to Australia for 1-3 months each time. Both in Sussex and Australia, this will mean work with mobile robots and ants in fieldwork settings. Additionally, visits to collaborators in Sheffield and some international travel to conferences or workshops may be required. 
Contract: fixed term until 03 January 2024
Reference: 10131
Salary: starting at £35,333 to £42,155 per annum, pro rata if part time
Placed on:  27 October 2022
Closing date:  22 November 2022. Applications must be received by midnight of the closing date.
Expected Interview date: TBC
Expected start date: 03 January 2023

Job description

We are looking for a post-doctoral research fellow to join our team working on bio-inspired AI and robotics who will develop novel active AI algorithms that are inspired by the rapid and robust learning of insects. You will join the prestigious £1.2m EPSRC International Centre to Centre Collaboration project: “ActiveAI: active learning and selective attention for rapid, robust and efficient AI.” and will work in collaboration with the University of Sheffield and world-leading neuroscientists in Australia.

Your primary role will be to develop a new class of ActiveAI controllers for problems in which insects excel but deep learning methods struggle. These problems have one or more of the following characteristics: (i) learning must occur rapidly, (ii) learning samples are few or costly, (iii) computational resources are limited, and (iv) the learning problem changes over time. Insects deal with such complex tasks robustly despite limited computational power because learning is an active process emerging from the interaction of evolved brains, bodies and behaviours. Through a virtuous cycle of modelling and experiments, you will develop insect-inspired models, in which behavioural strategies and specialised sensors actively structure sensory input while selective attention drives learning to the most salient information. The cycle of modelling and experiments will be achieved through field work in both Sussex and Australia.

You will work under the supervision of Professors Andrew Philippides, Thomas Nowotny and Paul Graham within the Department of Informatics at Sussex and will join an active team of research fellows and PhD students working on similar topics at Sussex.

Please contact Prof Andrew Philippides, for informal enquiries.

The University is committed to equality and valuing diversity, and applications are particularly welcomed from women and black and minority ethnic candidates, who are under-represented in academic posts in Science, Technology, Engineering, Medicine and Mathematics (STEMM) at Sussex.

Please note that this position may be subject to ATAS clearance if you require visa sponsorship.

The University of Sussex values the diversity of its staff and students and we welcome applicants from all backgrounds.

You can find out more about our values and our EDI Strategy,  Inclusive Sussex, on our webpages.

Download job description and person specification Ref 10131 [PDF 226.01KB]

The University requires that work undertaken for the University is performed from the UK. 

Visa Sponsorship Queries:

This role has been assigned an eligible SOC code and meets the salary requirements for Skilled Worker Sponsorship if full time. Please consult our Skilled Worker Visa information page  for further information about Visa Sponsorship. 

How to apply

Download our academic application form [DOC 199.50KB] and Personal Details and Equal Opportunities Form [DOC 119.50KB] and fill in all sections.

Email your completed application, and personal details and equal opportunities form, to  

You should attach your application form and all documents to the email in PDF format (we are unable to accept applications as or .pages) and use the format job reference number / job title / your name in the subject line.

You can also send your application by post to Human Resources Division, Sussex House, University of Sussex, Falmer, Brighton, BN1 9RH.

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