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. Identify key requirements, design and train AI-driven adaptation methods, and evaluate their effectiveness in both laboratory and real-world settings by working with players, developers, and accessibility
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not necessary as training will be provided. Experience of computer modelling is desirable but not essential as full training will be provided in an active and well-resourced research group based in
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The rapid electrification and digitalisation of society are creating increasingly complex electromagnetic environments. Fast-switching power electronics in vehicles, buildings, hospitals and farms can generate electromagnetic interference (EMI) that propagates through unexpected conducted and...
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data and archaeological signatures (e.g., circular mounds, linear ditches, rectangular foundations, etc.) tailored for AI applications – Feature engineering and representation learning to enhance
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knowledge, innovations, and solutions that help move the world forward. Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to
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for Scientific Research), Grenoble-INP (Grenoble Institute of Technology), and the University of Grenoble, affiliated with Inria (French National Institute for Research in Digital Science and Technology) and the
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related discipline. A strong foundation in at least one of: electrochemical or energy-system modelling, dynamic modelling and control, mathematical optimization, or data-driven modelling. Experience with
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information processing in event-driven sensing. Information Photonics is widely regarded as the key enabling technology of the 21st century and its application and use in many scientific and industrial fields
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-driven modelling. Experience with numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific
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Engineering, Control Engineering, Mechatronics, Robotics, or a related discipline with a strong focus on dynamic systems. Strong background in state-space modelling, estimation theory, and control systems. Good