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metres, including innovations in all that we do An environment encouraging curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster our staff’s soft and technical
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extrapolating loads along the substructure, for any type of turbine, given specific geometric, inflow and sea-state information. Furthermore, such a machine learning surrogate can speed-up both design and
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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locomotion. Apply machine learning and machine vision algorithms to track body and limb movements. Use biomechanical modeling to analyze walking data and fit locomotion models. Operate a force sensor to
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that the programme will combine ideas from a broad range of disciplines, including machine learning, control theory, differential equations, port-Hamiltonian systems theory, modelling of power systems, digital signal
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Devices - Photovoltaics) and high-performance computation (IET-3: Institute of Energy Technologies - Theory and Computation) towards the overarching aim of implementing an inverse design approach for novel
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influence motor system function and learning in healthy people of different ages. This cutting-edge approach will provide new information on the neurophysiological basis of synchronised brain oscillations and
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experimental approach gives us the opportunity to get detailed information about the dynamics of molecular collisions. In this project, you will perform reactive scattering experiments, design and implement
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scientific publications, and complete a dissertation within the project period During the first months of the appointment, the successful candidate is expected to prepare a plan for the progress of the work
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, development of data (pre-)processing pipelines, and machine learning model training to identify relevant biological states of the liver (e.g., healthy, recovering, not healthy). The (soft) sensor development