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/or reactor physics Documented knowledge/experience in machine learning What you will do As a PhD student, you will have the opportunity to shape your research project while receiving guidance and
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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synchrotron infrastructure tools for ex-situ and in-situ experiments to acquire essential information regarding the microstructure and the physical mechanisms involved during thermomechanical loading
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physics and strongly interacting systems? As a PhD student in theoretical nuclear physics, you will have the opportunity to explore deep questions about the origin and properties of atomic nuclei and the
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passive and active flow control algorithms, potentially incorporating machine learning/AI, to enhance aerodynamic performance and stall delay with rapid response times. The research is conducted in
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the reach of conventional computers. These challenges span fields such as optimization, quantum chemistry, materials science, and machine learning. Building a quantum computer requires a multidisciplinary
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, computer science, or similar topics. Experience with optimization, data-driven or machine-learning skills are meritorious. The candidate must have the PhD degree in hand before enrollment, but it is not required
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Reference Number 304--1-13691 Is the Job related to staff position within a Research Infrastructure? No Offer Description We invite applications for several PhD positions in experimental quantum computing
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research activities, this position comes with funding for a PhD student for whom you will be the main supervisor, and also a postdoctoral researcher, enabling you to build and lead a strong research team
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computationally hard problems are found, e.g., in optimization, quantum chemistry, materials science, machine learning, etc. Main responsibilities As a postdoctoral researcher, you will conduct high-quality