Research Fellow in Computational Neuroscience and Bio-Inspired Artificial Intelligence Ref 10735
School/department: School of Life Sciences
Hours: Full-time. Part time hours considered.
Requests for flexible working options will be considered (subject to business need).
Location: Brighton, United Kingdom
Contract: 17 months in the first instance
Reference: 10735
Salary: starting at £35,333 to £42,155 per annum, pro rata if part time
Placed on: 14 February 2023
Closing date: 09 March 2023. Applications must be received by midnight of the closing date.
Expected interview date: to be confirmed
Expected start date: Mid March or early April 2023
Job description
We are looking for a post-doctoral research fellow to join our team working on bio-inspired AI and computational modelling of insect behaviour and learning. You will join a BBSRC funded project called “Emergent embodied cognition in shallow neural networks”.
Your primary role will be to develop simulations of learning problems that insects face such as flower learning or navigation. Insect learning occurs rapidly within shallow neural networks. This is possible because learning is an active process emerging from the interaction of evolved brains, sensory systems and behaviours. We will explore how behavioural strategies and specialised sensors interact with learning success.
You will work under the supervision of Prof Paul Graham (School of Life Sciences) and Professors Andrew Philippides and Thomas Nowotny (Department of Informatics). You will join an active team of research fellows and PhD students working on similar topics.
Please contact Prof Paul Graham, p.r.graham@sussex.ac.uk, 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.
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 10735 [PDF 189.19KB]
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."
“Please note that this position may be subject to ATAS clearance if you require 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 jobapps@sussex.ac.uk
You should attach your application form and all documents to the email in PDF format (we are unable to accept applications as google.docs 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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