115 computer-programmer-"https:"-"Inserm" "https:" "https:" "https:" "https:" "https:" "https:" "P" Postdoctoral positions at University of Oxford in United Kingdom
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We are seeking two full-time Postdoctoral Research Assistants in Machine Learning to join the Foerster Lab for AI Research group at the Department of Engineering Science (central Oxford). The post is funded by ERC (or UKRI) and is fixed term to 31 December 2028. We are seeking two candidates...
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computational fluid dynamics and wind turbine fluid mechanics together with the ability to understand the aerodynamics of wind energy generation and floating body dynamics is essential. Informal enquiries may be
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, computer science, statistical or population genetics, or a related discipline), and a strong motivation to work on problems in genetics and you will also have relevant coding experience with producing high-quality
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experience in understanding eukaryotic microbial diversity. You will possess sufficient specialist knowledge in the discipline to work within established research programmes. Excellent communication skills
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channel research including biophysical, physiologial and pathophysiological knowledge to work our established research programmes. You should also be able to demonstrate your ability to manage your own
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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
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Applications are invited for a Postdoctoral Research Assistant in Astrophysics (ERC RedH0T). This project will be part of the ERC Synergy Grant “Red-Teaming the Hubble Tension” (RedH0T). The goal is to determine whether the Hubble tension arises from observational issues or from limitations in...
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research programmes, for example knowledge of cancer biology, hypoxia-mediated biology, redox, and the tumour micro-environment. You will have experience of cell viability assays, western blotting, qRT-PCR
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on combining theoretical and computational approaches (including data-driven mathematical models, tools for identifiability analysis and uncertainty quantification) to understand fundamental aspects
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, computational neuroscience, biomedical engineering, or a closely related quantitative STEM discipline. A strong background in cognitive, behavioural, and/or systems neuroscience, with relevance to learning