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Bayesian methods, deep learning, deep generative models, reinforcement learning, graph neural networks. Interviews are expected to happen in July 2025. Applicants are encouraged to guarantee that referees
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, the postholder will estimate the impact of applying ethnicity-dependent risk thresholds compared to a universal threshold on the outcomes of risk-stratified screening. The role involves collaboration with
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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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decade, along with measurements/estimates of local conditions and emissions for said flights. By comparing to an observational counterfactual, you will seek to establish whether cirrus properties
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effect can be predicted. You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past decade, along with measurements/estimates of local conditions and emissions
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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, and Internet-of-Things / Industry 4.0 technologies. Knowledge of computer science principles and modern AI approaches in computer vision and/or time series analysis is a plus. The position requires
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areas, and be able to creatively combine disciplines to make new research advances in fluid mechanics. You will be creating data-driven algorithms which can solve state estimation problems in fluid