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computer science and control systems architecture, advancing all the above disciplines. Building energy flexibility is an important resource for balancing and load shifting in energy networks, especially
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Job Description Are you ready to launch your scientific career by addressing the urgent need of renewable energy integration? At DTU Construct you will break new ground at the forefront of what is possible in the field of energy storage. We invite applications for a fully funded PhD position in...
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computer science and control systems architecture, advancing all the above disciplines. Building energy flexibility is an important resource for balancing and load shifting in energy networks, especially
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Job Description Do you have a background in bioinformatics or AI/ML? Do you wish to do a PhD whereby you use your computational skills to discover new insights in industrially important bacteria that can then be tested quickly in the lab rather than remain computational predictions? Do you also...
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following qualifications: Programming skills and AI interest Data analytical skills and computer science focus Experiences with chemical analysis and pilot experiments is an advantage. Knowledge
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degrees in either the natural sciences (chemistry, physics, mathematical/computational biology) or in the formal sciences (statistics, computer science, mathematics), but must have a serious interest in
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., Architectural, Electrical, Mechanical or Industrial Engineering, Autonomous Systems, Computer Science, Medical Engineering, and Human Psychology) More detailed information about the Rules related to DTU’s PhD
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section Energy Technology and Computer Science, where you will have around 20 colleagues with a mix of research and industrial experience. We work with research, innovation, technology implementation, and
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will, in addition, sharpen your didactics skills through experience as a teaching assistant. You must hold a two-year master's degree (120 ECTS points) in Robotics, Electrical Engineering, Computer Science
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of increasingly renewable energy systems. The ideal candidate will have experience or an interest in the following areas: Knowledge of computer science and machine learning. Familiarity with electrical and