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(a) networked multi-agent human-robotic systems that work collaboratively in a well-coordinated and safe manner, (b) computational design and digital manufacturing of components, (c) design of
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of opportunity to a variety of careers within the private and public sectors. The program includes the drafting of a PhD thesis, active participation in research networks, PhD courses and knowledge
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loads — EV fleets, residential batteries, smart heat pumps, and data-center clusters — across distribution and transmission networks is critical to unlocking deep decarbonization and maintaining grid
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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projects is required. Qualifications The ideal candidate has: A strong background in manufacturing engineering, management engineering, operations management, robotics, industrial engineering, computer
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willingness to collaborate, network, and interact with other researchers, and the ability to disseminate research in seminars, conferences, and teaching classrooms. We expect you to lead and undertake
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programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by prof. Patrizio Mariani, Dr. Jon Christian Svendsen and Dr. Fletcher Thompson We offer DTU
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horizons for advanced technologies. Responsibilities and qualifications The PhD project will focus on the design, synthesis, and characterization of new types of metal-organic network structures, which