72 machine-learning-phd-in-denmark Fellowship positions at University of Nottingham in Uk
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the University’s international reputation as a hub for cutting-edge research. Candidates must have a PhD degree in Power Electronics, Machines, and Drives or a closely related field, with a proven track record in
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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, Machines and Control (PEMC) Research Institute in the Faculty of Engineering. You will pursue a research plan in developing innovative modular power converter topologies and control for integrated motor
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, Machines and Control (PEMC) Research Institute in the Faculty of Engineering. You will pursue a research plan in heterogeneous integration-based activities regarding power semiconductor bonding, interconnect
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Bezares (numerical relativity), Dr Stephen Green (gravitational waves, data analysis including machine learning, black holes), Dr Laura Sberna (gravitational waves, black holes, and environmental effects
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engineering and have or be in the process of obtaining a related PhD and a track record of successful research. They will be computer literate with strong communications skills and a proven ability to work as
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contribution to the direction of research programmes in the Power Electronics, Machines and Control (PEMC) Research Institute in the Faculty of Engineering. You will pursue a research plan in developing
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technologies and make a key contribution to the direction of research programmes in the Power Electronics, Machines and Control (PEMC) Research Institute in the Faculty of Engineering. You will pursue a research
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expertise in a supportive and innovative environment. In this role, you will lead the computational strand of the project, applying molecular simulations, data analysis, and machine learning to uncover how
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their research portfolio Candidates must hold a PhD, or be near to submission of a PhD, in a relevant field of Microbiology, ideally involving Fungal Biology/Medical Mycology. They must understand microbial