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) 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 of teaching and
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. Our research brings together social theory, empirical studies guided by a range of interpretive methodologies, and the critique as well as advancement of interventions and social policies. We
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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role in this public-facing co-productive knowledge landscape. This position will contribute to the development of digital and face-to-face methods for public involvement, by shaping the theories
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process thanks to the use of Deep-Reinforcement Learning (DRL) to orchestrate the joint use of multiple attack surface tools, Large-Language Models (LLMs) to refine their configurations and graph-based
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theory for liquid crystal flow as well as theory for viscoelasticity of polymeric liquids. Both in the practical and simulation/theory work you will be guided and supported by post-docs and senior
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large-scale MD simulations, ideally with LAMMPS, demonstrated via corresponding roles in publications Experience with density functional theory (DFT) calculations, ideally with VASP, demonstrated via
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) Position Description: Position Description Two postdoctoral positions, 1) in differential geometry, and 2) in smooth dynamics and transformation groups. The Department of Mathematics at the University
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Applications should include: Curriculum Vitae Cover letter 2 selected publications from your PhD thesis Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be...
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and