679 proof-checking-postdoc-computer-science-logic Postdoctoral positions in United Kingdom
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defence and security, working directly with industry and sometimes governmental or military collaborators. You are expected to have strong mathematical and programming skills, knowledge of computer vision
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choice theory, or computational modelling. This post is based at the Department of Computer Science and on-site working is required. Remote and part-time working is possible in agreement with Professor
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View All Vacancies Reference: UOH-TA-429 Campus: Hybrid Faculty/Area: Faculty of Science and Engineering School/Department: School of Environmental Sciences Subject Group/Team: Geography and
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of climate science, statistical methodology, and computational modelling. The PROTECT project is part of the ARIA-funded programme on climate tipping points and aims to improve the scientific and statistical
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techniques. Analyse experimental data using statistical tools and computational methods. Collaboration & Mentorship: Collaborate with interdisciplinary teams of researchers and students. Mentor graduate and
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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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Full-time: 35 hours per week Fixed-term: 12 months The Opportunity: We are looking for a researcher to join our group at the Centre for Science at Extreme Conditions (CSEC), belonging
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programme as part of the collaborative NINEDTP. The Department’s research strategy is built around five themes: Communities and Social Justice; Health and Social Theory; Higher Education and Social
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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computational, a good understanding of practical molecular biology will be important. It is expected that the holder of this post will take a leading role in producing analyses for publication and dissemination