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or statistical machine learning. They will have excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings
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We are seeking a full-time Postdoctoral Research Assistant in Machine Learning and Power Systems to join the Energy and Power Group at the Department of Engineering Science (Osney). The post is
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of materials (e.g., combining structure prediction and machine learning). For example, we work closely with experts in computer science as part of the Leverhulme Research Centre for Functional Materials Design
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of materials (e.g., combining structure prediction and machine learning). For example, we work closely with experts in computer science as part of the Leverhulme Research Centre for Functional Materials Design
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the acquisition and analysis of (clinical) MRI data, as well as with mathematical modelling, image processing methods and/or machine learning. Experience of methods used for quantitative MRI and/or previous hand-on
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We are seeking a full time Postdoctoral Research Assistant in Safe Machine Learning for Power Systems to join the Foerester Lab for AI Research (FLAIR) at the Department of Engineering Science
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, or relevant subjects. Proficient in at least one or two of the following skills: machine learning/deep learning, cyber security, embedded systems, data science. Good communication skills Ability to work
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experience: Essential criteria PhD awarded in Computer Science, Machine Learning, Biomedical Engineering, Mathematics, or a related subject area * First or Second-Class Honors in mathematics, physics
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To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD awarded in Computer Science, Machine Learning, Biomedical Engineering
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) Advanced statistical evaluations (in particular machine learning-based analyses and research syntheses such as scoping/systematic reviews, meta-analyses and meta-science approaches) Leading functions in data