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The Kelly lab welcomes individuals with diverse career backgrounds – PhD-level scientists in any discipline with expertise in data and programming, or software engineers outside of academia looking to change
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frameworks and transformer architectures applied to biological sequences would be advantageous. You should have a PhD in bioinformatics, evolutionary biology, machine learning or similar. The post fixed term
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. Successful candidates should hold a PhD (or be close to completion) in a relevant area of astrophysics or physics, and should have experience in Type Ia supernova cosmology (e.g., supernova modelling
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prison sites, recruitment and data collection, and complex data analysis. You should have a PhD (or near to completion) and an Undergraduate degree in psychology or a relevant discipline. You will have
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-contractual basis) that combines a mix of remote and regular on-campus working. The salary for this post is £41,064 to £48,822 per annum. Your skills and attributes for success: PhD in neuroimaging, psychology
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of collaborative projects, working closely with clinicians, imaging experts, and computational scientists across the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics
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the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics, Statistical Machine Learning, Deep Generative Modelling, or a closely related field, together with relevant
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should have a MRes or PhD (or submitted at time of appointment) together with a strong academic track record, in a relevant area (e.g., Neuroscience, Medicine, Genetics, Mathematics, Engineering, Computer Science
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detection models, with a focus on achieving generalisable multimodal understanding in zero-shot settings. About You The successful candidate must have a PhD (or equivalent) in the field of computer vision or
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of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics, all departments highly rated in research activities and a wide-ranging portfolio