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Field
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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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procedure. About the organisation The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development
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challenges in high-speed electrical machine design for electrified transportation and power generation. Together, we will make technological advances that support the global transition toward net-zero
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Europe | 27 days ago
manufacturing, development of machine learning algorithms and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen
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Contract: Full Time/Fixed Term for three (3) years.Supervisor:Dr Mohamed Lamine Faycal BELLAREDJ, Assistant ProfessorDepartment of electrical engineering, Universite de Moncton (Moncton campus)Email
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electrical/mechanical engineering. Expertise in numerical electrical machine design tools (Ansys, JMAG, .etc) as well as corresponding scripting skills are desirable. Experience in electrical machine prototype
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development (using both traditional signal processing and machine learning), antenna design, and system hardware development. We collaborate closely with clinical experts to develop innovative technologies
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representations are developed. In particular, the project will support designers to achieve driver and passenger experiences that surpass current best-in-class benchmarks. Beyond the automotive sector, the project
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generation, storage, electric vehicles, smart energy management systems, etc.) and how to design the right incentives for a welfare-maximizing e-mobility integration (e.g., tariffs, subsidies, nudges, etc
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current best-in-class benchmarks. Beyond the automotive sector, the project might also contribute to our understanding of how other spaces can be designed to support the required user experiences