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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
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are looking for a highly motivated and skilled PhD researcher to work on graph-based machine learning surrogates of wind energy systems. Our goal is to accelerate flexible fatigue load estimation
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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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networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our
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should have strong digital signal processing and mathematical backgrounds evidenced by grades and/or prior publications. Additionally, the candidate should have expertise or strong interest (evidenced by
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in AI: Generative Diffusion & 3D/4D Scene Synthesis: Re-design diffusion and NeRF-style models so multiple agents jointly reconstruct a scene. Semantic-Aware Compression & Network Information Theory
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of economics and development. Position You will work actively on the preparation and defence of a PhD thesis in the field of economics and development. The PhD project will use theory and survey experiments
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-regulatory networks. Following cis-GRN network reconstruction and formal graph analysis, we will identify key regulatory factors governing cell-type specific response to CMT-causing mutations. Finally, we will
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students who are eager to develop and apply artificial intelligence techniques and mechanistic mathematical models to explore fundamental questions in biology. The PhD program is organized in partnership
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students who are eager to develop and apply artificial intelligence techniques and mechanistic mathematical models to explore fundamental questions in biology. The PhD program is organized in partnership