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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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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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ambitions to work in Data Science and/or clinical trial. The post holder will hold a PhD in medical statistics, Bio-Mathematics, epidemiology, or another quantitative discipline, and will possess strong
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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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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
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scientific articles for publication in leading peer-reviewed journals. Candidates must hold, or be about to obtain, a PhD in engineering, applied mathematics or a related subject area, with a major component
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scientific articles for publication in leading peer-reviewed journals. Candidates must hold, or be about to obtain, a PhD in engineering, applied mathematics or a related subject area, with a major component