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About the role We are seeking a talented Postdoctoral Researcher with expertise in healthcare AI to join the Modernising Medical Microbiology (MMM) Unit at the University of Oxford. This is an
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3.5-year D.Phil. studentship Project: Efficient engineering and control of predictable and reliable biotechnologies. Supervisors: Prof Antonis Papachristodoulou and Prof Harrison Steel This project will focus on solving challenges at the interface of Synthetic Biology, Control Engineering, AI,...
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The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world-class centre of excellence. The Faculty of Theology and Religion is seeking to recruit
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represent the research group at external seminars and conferences. To be considered, you must hold a PhD/DPhil in statistical genetics, quantitative genetics, bioinformatics, computer science, statistics
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strong connections with academics studying sustainability at many other universities such as at the University of Cambridge, University of Oxford, London Business School, HEC Paris, and Imperial College
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include research experience in maternal, perinatal, or paediatric fields, proficiency in other statistical software like R, and holding or nearing completion of a DPhil/PhD. Applications for flexible
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York, the Department of Computer Science at the University of Oxford, the Amsterdam Machine Learning Lab, and the XLA and JAX teams at Google. Your teaching Teaching will be a small but valuable part of
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around the world, for example at the University of Cambridge, University of Oxford, University of Sydney, University of Newcastle and Aalto University. We offer all our PhD students the opportunity to get
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models and is carried out in collaboration with Prof. Graham Ogg, the scientific partner from the University of Oxford. The funding for this exciting project was obtained within the FIRST TEAM programme of
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international partners including the Center for Computational Mathematics at the Flatiron Institute in New York, the Department of Computer Science at the University of Oxford, the Amsterdam Machine Learning Lab