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Field
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experience contribute to ongoing translational research program related to the application of statistical and machine learning methods in reproductive and perinatal medicine using both clinical quality
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servicing missions. Experience with machine learning techniques for robotic decision-making and intelligent control for tasks with high uncertainties. Experience with research on multi-agent collaboration and
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time role, 0.1FTE. The activities of this role will support development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning
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. You will also be responsible for implementing the model as a computer simulation and analysing it within a health-economics framework using standard computational techniques. You will also be
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, Information Science, Software Engineering, Data Science and Business Analytics. At the postgraduate level, we offer research master’s and PhD opportunities – including specialist taught masters in Artificial
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the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and