447 computer-programmer-"https:"-"U"-"UCL" "https:" "https:" "https:" "https:" "https:" "Dr" "L2CM" Postdoctoral positions in United Kingdom
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with relevant experience and will possess sufficient specialist knowledge in the discipline to work within established research programmes. They will also be expected to manage their own academic research and
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knowledge in the discipline to work within established research programmes. They will also be expected to manage their own academic research and associated activities and have previous experience
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research project within Dr Matheus Alves Duarte da Silva Wellcome Career Development project “How Did Infectious Diseases Become Wild?: Plague, Yellow Fever, and Disease Ecology in the Brazilian Hinterland
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cancer. This project will explore the role of tumour-associated macrophages (TAMs) in determining therapeutic responses to immunotherapy, with a focus on tumour immunity. The project is led by Dr Keaton
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We are looking for a Postdoctoral Research Associate reporting to the Principal Investigator Prof Yee-Whye Teh, they will be a member of the Oxford Computational Statistics and Machine Learning
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of this instrument ongoing, we make critical contributions to silicon sensor quality control, the initial steps of module assembly, thermal quality control of local supports. The group is led by Dr Seth Zenz, and
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programme and faculty priorities. The successful candidate will hold a PhD within the field of modern Arabic studies. They will be able to demonstrate an upward research trajectory and have experience
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is offered at the Deparment of Marketing and International Business (under the direction of Univ. Prof. Dr. Emmanuella Plakoyiannaki), Faculty of Business, Economics and Statistics at the University
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fields of research. They will be pursuing an independent programme of advanced study and research in Israel Studies, prepare research publications and publish high-quality research in peer-reviewed
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programme focused on applying AI‑driven analysis to in situ advanced microscopy of fibre‑based materials. The project aims to develop and deploy machine learning tools that extract real‑time structural and