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’. The role-holder will work closely with medicinal chemists at University of Oxford and pharmacologists at University of Glasgow, applying virtual screening, machine learning, AI-driven generative chemistry
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responsibilities will include: Explore innovative methods for food process optimization including the use of AI and machine-learning Develop and execute methods for characterizing and linking the texture and
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mathematics, statistics, or machine learning, or a closely related discipline • OR near to completion of a PhD • Expert knowledge of Bayesian computation and deep learning methods • Excellent
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digital health Computing systems and networks Cybersecurity Human-computer interaction Machine learning and artificial intelligence Software engineering Position details Positions are intended
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application of innovative Machine Learning (ML) frameworks to understand and predict the global hydrological cycle. The role will require bridging the gap between process-based physical modeling and scalable
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biology, mathematical and computational finance, numerical analysis, machine learning and data science or the Oxford Centre for Industrial and Applied Mathematics (OCIAM). The successful candidates will be
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transformations. Combining automated reaction discovery simulations, microkinetic modelling, machine learning, and global optimization, this project will develop a new and exciting route to addressing one
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with data linkage and working with routine healthcare data Experience with machine learning or AI applications in healthcare settings Advisory or consultancy experience Understanding of implementation
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, Organisational Behaviour, Statistics, Machine Learning, and so on; Excellent oral and written communication skills in English, including the ability to communicate with clarity on complex information. Excellent
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or machine learning. Excellent programming skills in Python and deep learning frameworks. A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal