63 condition-monitoring-machine-learning Postdoctoral research jobs at University of Oxford in Uk
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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machine learning, computer vision, human-computer interaction, or similar relevant areas. Experience in research or development on bias, interpretability, and/or privacy in machine learning/AI is necessary
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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We are seeking a Postdoctoral Researcher in Human-AI interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Chris
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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policy-influencing work. The post-holder also has lead responsibility for oversight and implementation of the Centre’s Monitoring Evaluation and Learning (“MEL”) programme and line managing the Centre’s
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the volcanoes of the Eastern Caribbean as a focal point and, with our international partners, will demonstrate how this knowledge can improve monitoring and warning systems in the Eastern Caribbean. The
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty