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Postdoctoral Research Assistant in Machine Learning
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This post is fixed-term for 2.5 years in the first instance.
We invite applications for a full-time Postdoctoral Research Associate to join the new Data-Driven Algorithms for Data Acquisition (DataAcq) project. This is a timely project developing new methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon Guarantee for an ERC Starting Grant awarded to Prof Tom Rainforth.
The post holder will undertake innovative research as part of the RainML Lab ) towards the goals of the DataAcq project. In particular, the post holder will be expected to undertake research related to one or more of the three work packages of the project: a) scalable and robust Bayesian experimental design, b) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models).
We proudly hold a Race Equality Charter Bronze Award and a departmental Athena SWAN Silver Award, which guide our progress towards advancing racial and gender equality. As part of our commitment to openness, inclusivity and transparency, we would particularly welcome applications from women and black and minority ethnic candidates, who are currently under-represented in positions of this type at Oxford. Applicants will be selected for interview purely based on their ability to satisfy the selection criteria as outlined in full in the job description. You will be required to upload a statement setting out how you meet the selection criteria, a curriculum vitae, and the contact details of two referees as part of your online application.
Please direct informal enquiries about the post to Tom Rainforth , quoting vacancy reference
Only applications received before 12.00 noon UK time on 10 July 2024 can be considered. Interviews are anticipated to be held on 1 August 2024.
£38,205 to £44,263 per annum. Grade 7
