Senior Research Associate

This research is funded by a UKRI-EPSRC Turing AI Acceleration Fellowship, which is part of the UK government's strategic investment in artificial intelligence research. This fellowship supports close collaborations with industrial stakeholders including, Microsoft Research, GCHQ, the Heilbronn Institute of Mathematical Research and the Alan Turing Institute. The PASCAL research programme is built on the foundation of probabilistic modelling and statistical learning to create a suite of algorithms, with theoretical guarantees on accuracy, that are capable of analysing large-scale data streams, learning deep latent data structures and providing trusted and interpretable decisions under uncertainty. As part of this research programme there is an opportunity to work closely with the project partners through research visits and secondments to gain real-world experience of industrial AI research.

You should have, or be close to completing, a PhD in Statistics, Machine Learning, or a related discipline. You will work directly with the principal investigator, Prof Christopher Nemeth, to undertake and support the research necessary to achieve the aims of the research grant. This will include, for example, publishing in leading statistics and machine learning journals/conference proceedings, presentation of research at workshops and conferences, developing code to implement new AI methods, and active involvement in project meetings. You will be experienced in one or more of the following areas: Bayesian statistics, computational statistics, statistical machine learning, probabilistic modelling. You will have demonstrated the ability to develop new statistical methodology and produce academic writing of the highest publishable quality is essential. Experience of developing research-level software is desirable but not essential.

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