726 computer-science-quantum-"https:"-"https:"-"https:"-"https:" positions at University of Oxford
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(CoI-AI) Programme. This ambitious programme combines advanced immunology, artificial intelligence, and human challenge models to transform vaccine discovery and accelerate development against major
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The post holder will join the Physical Oceanography and Palaeoclimate groups in the Department of Earth Sciences and perform numerical model data analysis relevant to two projects: MEZCAL and
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of technology, economy and our everyday life. Machines perform comparably to, or even surpass humans in playing board and computer games, driving cars, recognizing images, reading and comprehension. It is
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Contract & job type: Fixed-term for 3 years, full-time About us: At the Department of Physiology Anatomy & Genetics (DPAG) we undertake discovery science where we reassemble physiological processes
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of Immunity – Artificial Intelligence (CoI-AI) Programme, a pioneering initiative that integrates human challenge models, advanced microbiology, and artificial intelligence to accelerate vaccine discovery
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Studies. Working under the supervision of Professor Rita Abrahamsen (Chair of African Studies), the successful candidate will develop and pursue an ambitious and original programme of research within
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Thatcher Development Programme at Somerville College. The late Lady Thatcher, studied Chemistry at Somerville College Oxford from 1943 to 1946 and received bursary and scholarship support from the College
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First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline, and demonstrate
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biology, mathematical and computational finance, numerical analysis, machine learning and data science or the Oxford Centre for Industrial and Applied Mathematics (OCIAM). The successful candidates will be
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, economics, and other areas of computational social science; • AI scientists for natural science, integrating LLM agents with simulation and, where appropriate, robotic experimentation (e.g., automated “dry