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Python with demonstrable familiarity with PyTorch, experience in working on shared codebases, excellent applied math skills (especially probability theory, matrix algebra, calculus). Beyond technical
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epidemiology and statistical and mathematical modelling For appointment at grade 7: A4 Normally Scottish Credit and Qualification Framework level 12 (PhD) plus track record of emerging independence within a
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backgrounds such as in computer science, mathematics (pure or applied), or engineering. The successful applicant will be highly motivated, have excellent time management, and a proven track record in
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applicant must have (or be close to obtaining) a relevant PhD in Fluid Mechanics from an Engineering, Mathematics or Physics Department, a strong background in theoretical and computational fluid mechanics
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contributing positively to a collaborative research environment. Desirable: experience with building energy or power system applications, cooperative or coalitional game theory, or high-performance computing
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University’s EDI principles Qualifications Research Assistant First degree in engineering or numerate subject (e.g., mathematics, physical sciences, computer science) PhD close to completion in field of Power
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, Mathematics, Statistics, Biology, Engineering, Data Science or Computer Science. Main Duties and Responsibilities Perform the following activities in conjunction with and under the guidance of the Principal/Co
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the field of social or health sciences, bio/statistics, epidemiology or demography. Relevant experience in mathematical demography, statistics or other discipline with strong quantitative components
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studies and interactive AI systems. This position will be funded based on an initial 2-year contract + 2 years extension. The key idea is to apply theories, models, and methods from psychology to improve
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School/Department Computer Science and Mathematics Liverpool John Moores University (LJMU) is a distinctive, unique institution, rooted in the Liverpool City Region and with a global presence. Our