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candidate for a full-time (100%) PhD position for 3 years. You will join the research group Power Electronics and Electrical Machines (PEM) at IEL, where we foster an open, inclusive, and collaborative
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, Physics, Electrical Engineering, Communication Engineering, or equivalents; – Knowledge in artificial intelligence, statistical and machine learning, complex systems, agent-based modeling and simulation
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices
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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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Are you passionate about experimental aerodynamics and flow visualization? Apply for a PhD position that aims at transforming flow field measurements into aerodynamic forces by pressure and friction
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work on machine learning, AI security, and real-time embedded computing, with a strong emphasis on the AI and trustworthiness side of the problem. Tasks The PhD student will contribute to research
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, relating to craniofacial identification research and machine learning. You will require a computer science background. You will be applying AI and/or machine learning to Face Lab processes in relation
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at Aalborg University's Technical Faculty for IT and Design. In addition, the project involves close collaboration with the Department of Architecture, Design, and Media Technology and involves one other PhD
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ReDiLEEP training in response diversity methods, data management, reproducible code, R/Tidyverse, machine learning and AI for ecologists, visualisation, evidence-based policymaking, science-policy
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on psychological assessment of learning and attention disorders and neuropsychological testing with youth with various medical conditions (including seizures, cancer, and kidney transplant patients). The fellows