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Project title: Developing and Evaluating Interpretable Approaches for Human-Centered Machine Learning.Project description: Approaches in interpretable machine learning offer promise in understanding
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, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will have experience in one or more of these subject
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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, motivation to learn new skills as well as excellent written and oral skills is essential.Example publications from the Lab:•Detection of host cell microprotein impurities in antibody drug products. 2024 Nature
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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for candidates with exceptional skills and grades in engineering or physics and/or computer science and/or signal processing, with the strong and proven knowledge of machine learning and/or some expertise in
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integrated with the NiMARE (NMA) software project. To be considered you will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain