488 computer-programmer-"https:"-"U"-"UCL" "https:" "https:" "https:" "https:" "U.S" Postdoctoral positions in United Kingdom
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applicant will contribute to the development of novel mathematical and computational methods for image analysis and AI, with a particular emphasis on interpretable and uncertainty-aware approaches motivated
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Ref.: 533742 Work type: Full-time Department: School of Computing and Data Science (14700) Categories: Senior Research Staff & Post-doctoral Fellow Post-doctoral Fellow in the Department
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computational docking and/or AI-assisted predictive tools. All molecules will be screened using in vitro and cell-based platforms established in our team, and the best will be continued to more advanced models
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an interdisciplinary team led by Dr Peter Etchells. The successful applicant will be expected to plan and perform genetics, gene expression, and phenotyping aspects of the project. Key responsibilities: To understand
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an interdisciplinary team led by Dr Peter Etchells. The successful applicant will be expected to plan and perform genetics, gene expression, and phenotyping aspects of the project. Key responsibilities: To understand
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sensing. are essential as well as strong computing skills, including the knowledge of UNIX/Linux, Fortran, Python, or other high-level languages. The post is full time and fixed term for 18 months
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Postdoctoral Researcher. The group aims to identify, understand, and develop therapies for rare genetic disorders. The group is primarily computational but partners with multiple international labs (including
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handling of anhydrous hydrogen fluoride and the development of physical organic models to assess their reactivity. High level computational techniques will be used to aid understanding. This exciting
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Hopkins University (USA). About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for identifying high
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University (USA), and Google Deepmind (London). About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for