19 computer-vision-and-machine-learning Postdoctoral positions at University of Cambridge
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Fixed-term: The funds for this post are available for 12 months. Applications are invited for a Research Assistant (RA) to join the Prorok Lab in the Department of Computer Science and Technology
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. Familiarity with standard design verification (DV) procedures and continuous integration (CI) setups would be beneficial. Knowledge of machine learning workloads and the design of machine-learning accelerators
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interactions in the condensed phase and at surfaces, with a particular emphasis on the development and application of first principles and/or machine learning approaches. Research in the Michaelides group
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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research centre well-known for its close-knit community, friendly atmosphere, and outstanding research support. We are seeking a post-doctoral research associate with experience in computational approaches
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desire to learn others: molecular biology, C. elegans or other model organism research, confocal imaging, computational analysis, preferably in python and electrophysiology. We are also looking for someone
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modelling to study the causes and consequences of extreme chromosomal instability in these cancers. The role will involve: - Learning and applying cytogenetic methods for generation and analysis of chromosome
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bioinformatics/computer science will be essential. Prior experience with connectomics data is highly desirable. Our group has developed an international reputation in this area and our tools have now been used in
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the Jones team website (https://www.slcu.cam.ac.uk/research/jones-group ). Foundations in molecular biology and confocal microscopy are required, alongside a willingness and ability to learn and work with new
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of the research programme is to develop EHR common data model specifications and to advance knowledge in the field of psychiatry EHR research, including clinical risk prediction modelling. The appointee will work