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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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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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. You will be responsible for managing your own academic research, collaborating with computational and clinical researchers, and contributing to the scientific development of the lab. This is an exciting
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PhD in Chemistry or a relevant subject area, (or be close to completion) prior to taking up the appointment. The research requires experience in computational chemistry, including machine learning
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applications. In this role, you will take the lead on an independent project within our broader research programme. Your work will centre on identifying and characterising novel regulators of the immune response
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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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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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to implantation, including validating methods in virtual in vivo environments. • Collaborate with engineers to refine fuel cell specifications and support in vivo experiments. You should hold a relevant PhD
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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
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; and organising and deliver autonomous system trials and demonstrations at internal and external sites. You should possess a relevant PhD/DPhil or be near completion together with relevant experience