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performance (10–50 Hz) on hardware with constrained memory, power and compute. The project will investigate training, adapting and deploying compact Physical AI models efficiently. Work may cover vision
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
, the University of Copenhagen and the MAX IV synchrotron. You will work with an international team of mathematicians, crystallographers and data scientists. The project aims to transform small-molecule structure
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tuition fees and a tax-free stipend. Available to Home fee-status applicants only due to funding structure. Delivered in collaboration with Intel, including industrial co-supervision. The student will work
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work with a wide range of subsurface datasets, including well logs, seismic interpretation and published geological information, to map saline aquifer distributions from the Palaeozoic to the Mesozoic