612 computer-programmer-"https:"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "P" "Dr" positions at University of Oxford
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programmes, a proven ability to manage your own academic research and associated activities, experience of contributing to publications and presentations, and excellent communication skills, including
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and relationship-building. You will have experience of working in a research-intensive university (or in a directly comparable environment), supporting programmes, projects or initiatives, and
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-clinical immunology and vaccine development programmes, focused on outbreak-related pathogens including filoviruses such as Ebolaviruses, arenaviruses such as Junín, and Bunyaviruses such as Crimean–Congo
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excels in a wide range of research areas spanning basic science to translational research and clinical trials. It is committed to the provision of world-class graduate training programmes and actively
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growing department within the Medical Sciences Division. The Department of Paediatrics is a world leader in child health research and hosts internationally renowned research programmes in drug development
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are seeking a development opportunity, will be considered for an appointment at Grade 6 (£35,681 - £41,636 p.a.) with amended duties, a development plan and mentoring. Fixed Term (maternity cover) until July
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computing skills, including the knowledge of UNIX/Linux, Fortran, Python, or other high-level languages. The post is full time and fixed term until 31 December 2026. The closing date for applications is noon
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of tuberculosis vaccines in Oxford and plan, direct and undertake clinical delivery of research work in both tuberculosis and SARS-CoV-2 studies. You will be responsible for the screening, vaccination and challenge
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, reproducible model systems that underpin innovative scientific programmes. About you You will hold a degree in Biological Sciences (or a closely related discipline) and have relevant laboratory experience
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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