34 machine-learning-modeling-"Linnaeus-University" PhD positions at University of Nottingham
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Photovoltaic Modelling for Performance Optimisation Theme 3: AI-Enhanced Coordination of Renewable Energy for Smarter Grid Management Theme 4: Decoding Social Acceptance: The Community Lens on Large-Scale Solar
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behaviours of thin foils in vacuum and inert environments will be explored. Based on the results, a constitutive material model including the creep effect (time, temperature and load dependencies) will be
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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an assessment of the part quality; this will involve the development of laser beam processing on specific aerospace materials, and a model to understand the fundamental mechanisms of the process to identify
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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, chemistry, and be willing to learn new disciplines and innovate to achieve the project goals. Additionally, ideal candidates would also have interests in areas such as: 3D printing, materials sciences
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, chemistry, and be willing to learn new disciplines and innovate to achieve the project goals. Additionally, ideal candidates would also have interests in areas such as: 3D printing, materials sciences
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Manufacturing process for Cold Spray with Artificial Intelligence, operate the AM machine, characterise the materials with scanning electron microscopy and transmission electron microscopy with tensile testing
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PhD Studentship Aircraft Electrical Power System Stability This exciting opportunity is based within the Power Electronics and Machines Centre (PEMC) Research Group at Faculty of Engineering which