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for the Future of Intelligence (CFI). The candidate will contribute to teaching and lead a research programme in one or more of the following areas: ethical use of machine learning, AI safety, algorithmic
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(Biochemistry, Neuroscience) MSc degree (or equivalent) in Epidemiology, Biostatistics, Data Science or related discipline. Strong quantitative analysis skills and experience developing algorithms and/or
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the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real
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pivotal role in analysing large-scale genomic and clinical data, applying cutting-edge algorithms, and collaborating with renowned experts in the field. At PBCI, we believe in fostering a collaborative and
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A position exists for a Post Doctoral Research Associate in Department of Applied Mathematics and Theoretical Physics to work on the theory and implementation of algorithms and protocols on quantum
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the context of algorithmic problems related to constraint satisfaction and graph homomorphism and isomorphism problems. It brings to bear significant new mathematical (algebraic and topological) methods
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in our mission to develop clinically useful algorithms, drive high-impact publications, and pave the way for personalised breast cancer treatments. Analyse data from cutting-edge technologies
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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in applying and developing the theory and algorithms needed to simulate these challenging systems is an essential prerequisite. The successful applicant must have a PhD degree in theoretical chemistry