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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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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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of advanced X-ray methods to explore chemical, crystallographic and morphological changes that drive battery performance loss. You should possess a doctorate in a relevant engineering or physical science
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should possess a PhD/DPhil in engineering, physics or applied mathematics, and hold a strong publication record in your field. You should have expertise in numerical or experimental modelling (preferably
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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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on qualifications and relevant skills acquired and will also be determined by the funding available. About you Applicants will hold a PhD/DPhil or be near completion of a PhD/DPhil in a subject relative to Structural
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independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics, statistics, physics, engineering, data science or a related discipline, and have
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until 30 March 2026, and may be extended subject to the availability and renewal of external funding. With a background in materials science, materials processing or related engineering or physical
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We are seeking a full-time Postdoctoral Research Assistant in Batteries for Aerospace Applications to join Prof Paul Shearing’s research group at the Department of Engineering Science at Begbroke
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expected to be bioinformatic in nature. Applicants must have a PhD in a relevant subject, experience of macrosynteny analysis and phylogenetic analysis of gene families, and a thorough knowledge of animal