Location: | Sussex, Falmer |
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Salary: | £45,585 to £54,395 per annum (pro rata for part-time working), Research Fellow II |
Hours: | Full Time, Part Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 16th August 2024 |
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Closes: | 30th August 2024 |
Job Ref: | 31738 |
Applications are invited for a Research Fellow in Machine Learning at the Predictive Analytics Lab (https://wearepal.ai/) in the Department of Informatics at the University of Sussex. The laboratory is currently supported by 3 active EU grants: BayesianGDPR (ERC), TANGO (EU Horizon), and Act.AI (ERC Proof of Concept).
The position is part of the ERC funded project “Bayesian Models and Algorithms for Fairness and Transparency” (BayesianGDPR) – led by Professor Novi Quadrianto. It involves the development of novel inference and computational methods towards the realisation of fair and transparent machine learning systems in static and dynamic settings.
The successful applicant should have a PhD in machine learning in a field relevant to our research area such as active learning, online learning, stochastic optimisation along with a good publication record in leading machine learning publication venues. The salary offered will be appropriate to the qualifications, standing and experience of the successful candidate.
Informal enquiries are welcome and can be made to Professor Novi Quadrianto (N.Quadrianto@sussex.ac.uk).
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.”
For full details and how to apply see our vacancies page
The University requires that work undertaken for the University is performed from the UK.
The University of Sussex values the diversity of its staff and students and we welcome applicants from all backgrounds.
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