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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
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will have a PhD in a relevant scientific discipline and sufficient specialist knowledge relevant to the project to be able to make a start on day one – we do not expect everyone to have all the skills
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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
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part of a wider programme of work to establish that membraneless organelles, biological liquid droplets, are effectively regions of organic solvent, suspended inside cells and that the properties of each
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research will feed directly into the broader goals of this programme to assess the suitability of various approaches to GGR. About you You will hold or be close to a PhD in Aqueous/Environmental/Ocean
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the programme of research for publication in top quality peer-reviewed academic journals. In addition, you will provide guidance to junior members of the research group including research assistants, PhD students
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of a wider programme of work to establish that membraneless organelles, biological liquid droplets, are effectively regions of organic solvent, suspended inside cells and that the properties of each
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objects such as neutron stars and black holes. Strong computational experience and proficiency in simulations is highly preferred. The post-holder may be expected to help in the supervision of DPhil and
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will write research articles and present the results at national and international conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics
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projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification