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Training: Conduct Silvaco TCAD simulations (fabrication processes, device modeling, and circuit-level simulations) . Experimental Work: Participate in cleanroom processes, device fabrication, and electrical
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integration of model checking and synthesis with machine learning will provide the key to innovative, highly scalable methods for learning, analysis, synthesis and optimization of cyber-physical systems. Based
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Sustain and DTU FOOD), as well as two Departments at NTNU (Chemistry and Biology) will supervise and integrate the PhD fellow into several research communities. There will be an enhanced focus
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, section for Fluid Mechanics, Coastal and Maritime Engineering. The PhD project will play an integral part of the project “Marine advection and dissipation in the vegetated coastal environment”, financed by
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converters are increasingly deployed not only to integrate renewables, but also to control potentially flexible loads such as pumps, fans, EV chargers, and others. With their large energy consumption
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bottlenecks in data and system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models
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related programming and hardware circuit skills. This, as well as to research proper methods for educating teachers to apply knowledge, competences, and skills needed to conduct and develop effective and
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to material, cutting tools and parts production. The PhD project will therefore focus on the development of an integrated system combining direct and indirect tool wear monitoring for reliable residual life
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the opportunity to participate and influence the development of advanced power system models for renewable energy integration in collaboration with the top universities and industry in the field
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for Industrial Mechanics. This center is an integral part of the Institute of Mechanical and Electrical Engineering, situated in the vibrant city of Sønderborg. Together, they form a hub of technological