202 computer-security "https:" "https:" "https:" "https:" "https:" "Dr" research jobs at University of Oxford
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Health Bioethics Network, and the Oxford-Johns Hopkins Global Infectious Disease Collaborative (GLIDE). Reporting to Dr Tess Johnson and working closely with the Ethics, Policy and Context Theme of the PSI
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Gen(d)erations: Past stories, present perspectives and future approaches for trans and non-binary inclusion and belonging in medicine. Reporting to the Principal Investigator, Dr Debbie Aitken, the post
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joining the academic community at Oxford, please contact the Chair of the Faculty Board, Professor Martin Conway ( martin.conway@history.ox.ac.uk ), or the Senior Tutor at Magdalen College, Dr Mark Pobjoy
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We are seeking a talented and motivated postdoctoral researcher to join our Somatic Evolution Research group led by Dr Verena Körber . You will contribute in the research of somatic evolution during
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We are seeking to appoint a Research Assistant in Brain Tumour Biology to join Dr Pathania’s Laboratory at Ludwig Institute for Cancer Research, part of Nuffield Department of Medicine. The lab
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neuroimaging studies to investigate systemic effects of visual and circadian influences on the human brain. The position is funded by a Royal Society Dorothy Hodgkin Research Fellowship to Dr Betina Ip. The RA
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inclusion and belonging in medicine. Reporting to the Principal Investigator, Dr Debbie Aitken, the post holder will be a member of an interdisciplinary Medical Education research team and will contribute
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cutting-edge research at the intersection of Digital Sociology and Public Policy. The successful candidate will join a small but growing connected families research group led by Dr Ekaterina Hertog and Dr
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About the role The Department of Biology is seeking to recruit a Postdoctoral Research Assistant to work under the supervision of Dr Laura Moody. The post is funded by the Royal Society for one year
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly