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, This opportunity allows a postdoctoral researcher to work on an industrially facing project, applying artificial intelligence (AI) methods to better inform processing to obtain high-quality engineering polymers from
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of technology, economy and our everyday life. Machines perform comparably to, or even surpass humans in playing board and computer games, driving cars, recognizing images, reading and comprehension. It is
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frameworks is essential. Experience of working with UK Biobank imaging or similar large-scale population would be desirable. Diversity Committed to equality and valuing diversity Application Process You will
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, imaging, and 3D tissue model establishment will be essential to the role. Application Process If you would like to discuss this role, please contact Prof Eric O’Neill at eric.oneill@onccology.ox.ac.uk
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program exploring the role of fluctuations in molecular transport processes by studying highly controlled experimental models at the meso- and nanoscale, funded by a UKRI Frontier Research Guarantee Grant
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bioinformatics. The role will be responsible for developing and characterising human dorsal root ganglia cultures to benchmark the newly developed iPSC derived organoid model systems. This will include processing
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constituents of its microstructure. You will develop inverse-analyses of the in situ imaging experiments to extract the non-linear stress/strain relationships. You will design critical in situ X-ray and neutron
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collaborative programme bringing together a team of leading experts in advanced electron microscopy imaging, first-principles modelling, metal halide semiconductor thin-film and device fabrication, and
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motility apparatus through single molecule fluorescence imaging approaches. Underpinning genetic and biochemical experiments will also be required. The project will build on our recent work in this area
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Lives with Linear Accelerators) project, which aims to leverage technologies developed for particle physics, computer vision and robotics into a novel end-to-end radiotherapy system as an essential