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sustainable future for the built environment. You are expected to have technical skills and a broad knowledge of Engineering. More specifically, you are required to have: A PhD degree in a field relevant to the
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of the world’s most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close
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to advance their leadership abilities by proposing and supervising master student projects on the topic, as well as helping in the supervision of PhD students. The successful candidates will work with Prof
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Delft as well as in collaboration with the project partners. As candidate, you have a PhD degree in electrical engineering, materials engineering, micro/nanoengineering, physics or related fields. We
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and variable generation. Essentials: A PhD degree in a field with a strong emphasis on computer science, modelling and algorithms. Relevant mathematical frameworks include simulation modelling
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in the pursuit of our ambitious goals. And you will get all the support and training you need for your personal and professional growth. You hold a PhD (or will soon complete) in (bio)physics or a
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. Demonstrating autonomous barge performance and barge fleet operations, with respect to assessment of the developed algorithms using model scale vessels in controlled lab environment. You have a PhD degree or
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a PhD in aerospace engineering, applied mathematics, mechanical engineering or other related fields. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and
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instrument scientist position within three years. You hold a PhD in a subject related to physical science, life science, materials science, engineering or another relevant field. You have experience in
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. Candidates for this challenging project should have a PhD degree and background in e.g., systems and control, computer science, applied mathematics, electrical engineering, mechanical engineering, or chemical