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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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. These positions involve advanced numerical simulations and analysis of spacecraft data. The positions are full-time, 100% funded for four years and lead to a doctoral degree in Computational Physics. The expected
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PhD Studentship: Improved Heat Transfer Understanding via Conjugate Heat Transfer, Co-Simulation and AI Approaches Research has shown that the development of gas turbines is critical to the success
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and computational methods within quantum mechanics and statistical physics with the aim to design alloys for rare-earth-free high-performance permanent magnets. You will use computational techniques
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available in the further tabs (e.g. “Application requirements”). Objective The programme aims at fostering strong, internationally oriented higher education systems in Southeast Asia with the capacity
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Programme description: The ICN2 offers a competitive PhD Programme to talented students who wish to develop a research career at one of the top European institutions in the field of nanoscience and
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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by the Ada Lovelace Centre and the University of Birmingham. This interdisciplinary project is ideal for candidates with a background in physics, materials science, chemistry, or computational science
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applications from prospective PhD students who are interested in performing research in Mathematical and Theoretical High Energy Physics. The PhD work will be carried out in the group of Prof. Alba Grassi