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degree in Hydraulic Engineering, Hydropower Engineering, Civil Engineering, Fluid Mechanics or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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in control systems and fluid-structure interaction. The students will be supervised by Prof Khac Duc Do and the co-CIs of the project. Student type Future Students Faculties and centres Faculty
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1 August 2025 or as soon as possible. You can read more about career paths at DTU here . Further information Further information may be obtained from Prof. Jochen Teizer at teizerj@dtu.dk . You can
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Supervisors: Prof. Reinhard Maurer, Prof. Scott Habershon In drug discovery, millions of molecules need to be screened for their viability as drug candidate, including their synthetic viability
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Supervisors: Dr Raj Pandya, Prof. Nicholas Hine, Prof. Reinhard Maurer While we as humans are used to seconds and hours, electrons and atoms in materials move a whole lot faster around a million
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Supervisors: Prof. Reinhard Maurer (Chemistry), Prof. Richard Beanland (Physics) Understanding how local atomic structure and long-range emergent magnetic and electronic properties in defective 2D
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Supervisory Team: Prof Neil Sandham PhD Supervisor: Neil Sandham Project description: This project is focused on scale-resolving simulations (large-eddy and direct numerical simulation) combined
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I offer projects broadly related to supernova explosions and the final stages in the lives of massive stars. Specific topics of interest include fluid dynamics processes in stellar explosions and
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28.07.2023, Wissenschaftliches Personal Prof. Karen Alim’s group on Biological Physics and Morphogenesis at the TUM Campus Garching uses theoretical and experimental methods to investigate how flow