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operational data and machine learning. You will be based at UCL mechanical Engineering, and collaborate with industry and port partners on system design, prototyping, and lab-based trials. Key responsibilities
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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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: “To learn and to apply, for the benefit of mankind”. Ranked among the top 100 universities globally by well-known ranking organisations such as Quacquarelli Symonds (QS), Times Higher Education (THE) and U.S
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Liverpool where, in the School of Computer Science and Informatics, we have an active group of PhD students, postdocs, and academics working at the intersection of Machine Learning, Verification and
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one of the following analysis techniques (multiple preferred): normative modelling, dimensionality reduction techniques, machine learning, deep-learning, state space modelling, advanced statistics
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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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will strive to continually excel as an innovative world-class university that makes a positive impact on society, living up to the University’s motto: “To learn and to apply, for the benefit of mankind
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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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: Research Data Collection: Create and monitor online surveys using REDCap, conduct participant interviews, and assist with project development and ethics applications. Collaborate with Stakeholders: Work