351 phd-computer-science-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at University of Cambridge
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of our key research directions relevant for this position. Candidates should have (or be near to completing) a PhD in Computer Science or a related subject, or relevant experience. A high degree of
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possible extension subject to funding). The group works at the interface of clinical and laboratory science, aiming to better understand and develop novel treatments for neurological disorders. In particular
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, cultural practices and technologies between China and the Mediterranean or any sub-region between the two at any period up to the present day. This Research Fellowship is part of a broader programme, which
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are invited for the 2026 Research Fellowship awards. Up to four Research Fellowships will be awarded in this competition. Applicants should have submitted their PhD after 1 October 2024, or be on track
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Practitioners with experience in clinical neurology at greater than ST3 level, who hold a PhD in clinical neuroscience/biological sciences. Experience in clinical trials is desirable. Click the 'Apply' button
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of an integrated approach to risk-stratified screening, following the success of the BRAID trial. This work will help inform NHS Breast Screening Programme policy, assessing the value of supplemental imaging based
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Sciences (HSPS) and also has a vibrant MPhil and PhD programme. There are currently about 80 students working on PhDs on a diverse range of topics in sociology. Further information about research interests
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neuroscience, with the aim of improving mental health outcomes in both non-clinical and clinical populations. We are based at the MRC Cognition and Brain Sciences Unit, University of Cambridge, a world-leading
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The Sciences Research Fellowship is offered in any field of Science, Mathematics, Engineering, or Psychology. Applications for the 2025 Fellowship have closed. The next round of recruitment will
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-generation AI hardware (ASIC) accelerators. The UK's Advanced Research Invention Agency (ARIA) is supporting an ambitious programme of work that aims to reduce the the cost of AI by more than 1000x: https