227 computer-programmer-"https:"-"Prof"-"https:"-"https:"-"https:" Postdoctoral positions in United Kingdom
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interdisciplinary research and teaching at the intersection of the humanities and computational methods. The successful candidate will join the Computational Humanities research group, a vibrant and collaborative
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proven expertise in seismic data processing and analysis, knowledge of volcanic/ geothermal processes, strong quantitative skills, and proficiency in Python for scientific computing. You should be
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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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About the department Our vibrant Faculty of Media, Science & Technology encompasses a wide range of disciplines across four Schools: the School of Computing & Engineering, the National Centre
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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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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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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