80 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "IMEC" Postdoctoral positions at University of Oxford
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expertise in deep learning and representation learning applied to biological data, experience with large-scale multi-omics datasets (such as single-cell and proteomics), and strong programming skills in
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experiment will be an advantage. Candidates are expected to demonstrate the ability to communicate effectively, plan and execute research activities, and work in a team. Please direct enquiries about the role
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drawn from a variety of experimental approaches, refining research directions as appropriate. In addition to driving their own research programme, the appointee will contribute to the generation of new
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Equality, Diversity and Inclusion Strategic Plan, our commitment to equality and diversity goes hand in hand with our commitment to academic freedom and free speech.
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towns programme, organise and run patient and public involvement events to engage with community members and innovate, contribute to and promote the research, publication and impact focus of the centre in
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will contribute to an exciting, interdisciplinary programme developing next-generation human in vitro models of pain. The project aims to recreate the complex multicellular interactions that underlie
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development towards optimizing and understanding sonochemical nitrogen fixation to help advance our internationally leading programme of research. This work will also contribute towards building a case for a
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by ATi/Innovate UK and Rolls Royce and is fixed-term to June 2029. You will join a world‑leading programme advancing experimental and numerical methods to predict the impact performance of composite
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cell-based assays. You will possess strong experimental design and data analysis skills, with the ability to independently plan, execute and troubleshoot complex experiments. You will have highly
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programming; running an imaging study; blood-brain barrier evaluation; and/or the application of machine-learning methods to large (ideally imaging) datasets. Informal enquiries may be addressed to Professor