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We are seeking a Post-doctoral research associate to investigate the mechanisms of mutagenesis in the human genome. The Opportunity: To lead a programme of original, high-quality research focusing
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. Ready to be part of our team? Let’s shape the future together! About the team: The Computational Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning
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to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across conventional boundaries and pursue hypothesis-led
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the performance of lithium ion technologies. To support the programme, the post holder will be required to carry out research on characterisation of battery degradation, with a particular focus on the application
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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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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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Contract: 36 months, full time An exciting opportunity has arisen for a Postdoctoral Researcher to join the Howard Group, working on cutting-edge science in the field of Computational and Systems
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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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. Computing time is available on our local cluster and on the Vienna Scientific Cluster (VSC), a supercomputer shared by Austria's major universities. We focus on the development of methods to solve the many
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion