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requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Associate Professor Birgitte Zeuner
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requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment will be made by Associate Professor Christian Damsgaard, Professor Jakob
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deformation. Responsibilities Develop scientific machine learning methods in close collaboration with team members specializing in experimental techniques and materials science. Utilize unique experimental data
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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
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professional network through international research stays and develop innovative solutions that support the global transition to sustainable energy systems. Apply now to make a difference in the field
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limited. We are offering a PhD scholarship for a student to develop ambitious new machine learning strategies for generating AI-ready data. You will work at the frontier of active learning and ML-guided
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) develop and optimize extraction techniques using enzymes in combination with non-thermal technologies such as ultrasound, ohmic heating, and pulsed electric fields, (iii) evaluate the techno-functional
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power. Your primary tasks will be to: Develop a detailed 3D multiphysics model of the HT-PEMFC stack to analyze and optimize thermal management. Design a heat recovery system, tailored
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of the English language and communication skills, with the ability to present results in scientific papers. We welcome candidates with varied experiences and educational pathways. DTU Wind works with an inclusive mindset
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assist in preparation and testing of the platforms at the partner institutions collaborate with an interdisciplinary research team in a focused scientific effort contribute as teaching assistant at DTU