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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine
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, experience managing and analysing ancestrally diverse genomic datasets, and expertise in computational genetics, including variant annotation and genome-scale analyses. Proficiency in R or Python, excellent
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the starting date is negotiable. The current funding is guaranteed from the Montague Burton Fund. We are looking for a candidate who is a health economist with excellent computational skills. The post is
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will have or be close to the completion of a PhD in Neuroscience, Psychology or a closely related discipline. With in-depth knowledge of cognitive and computational neuroscience including motivation
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bioinformatics/computer science will be essential. Prior experience with connectomics data is highly desirable. Our group has developed an international reputation in this area and our tools have now been used in
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) programme . This is a fixed term position until March 2026. About STARSand HSMA and the work you will be involved with. STARS is an Open Science project that aims to increase the quantity and quality
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C and python, familiarity with
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the Department of Engineering Science at the University of Oxford. The post is funded by the Oxford Martin Programme on Circular Battery Economies. It is fixed term up to December 2027. You will undertake
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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Metabolism (OCDEM) on studies related to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across