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you will be a member of the Mathematics Institute. About You The successful candidate is likely to have a strong background in mathematics, statistics, computer science, physics or engineering
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PhD (or nearing completion) or possess an equivalent qualification/experience in a related field of study, which may include (but is not restricted to) mathematics, physics, computer science, biophysics
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; Chemistry; Computer Science; Ecology; Engineering; Environmental Sciences; Mathematics/Mathematical Sciences; Medicine; Natural Sciences; Physics; Psychology; Veterinary Sciences. This Fellowship is intended
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to candidates with a strong quantitative background. We welcome applicants with training in mathematics, statistics, health economics, computer science, or epidemiology, particularly those with good numeracy and
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the essential criteria for the post, which includes: Have or be about to obtain a PhD in computer science, engineering, mathematics or physical sciences area. Recent high quality research experience in
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of women in science, mathematics, engineering and technology. We strongly support UCL’s Equalities and Diversity Strategy, and encourage applications to our vacancies from under-represented groups. Customer
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computer science, engineering, mathematics or physical sciences area Recent high quality research experience in machine learning/AI, or both, as evidenced by a strong track record of publications in leading
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of The University of Glasgow Inference Dynamics and interaction Research group, in the School of Computing Science, including establishing and sustaining a track record of independent and joint publications
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particularly suited to candidates with a strong quantitative background. We welcome applicants with training in mathematics, statistics, health economics, computer science, or epidemiology, particularly those
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obtaining, a PhD in computer science, engineering, mathematics, or a related physical sciences discipline, with research expertise in areas such as hardware-aware AI security, approximate computing, or secure