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prediction of gene perturbation effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural
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and implement Bayesian graph neural networks and convolutional neural networks as surrogates for high-fidelity biomechanical models Quantify and propagate uncertainty, and develop strategies for model
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Contribution to feasibility studies in architecture and urbanism in the context of Luxembourg Teaching territorial design, urban design or architectural design as well as theory of urbanism and/or architecture
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role Research in the general domain of stochastic analysis, with special focus on stochastic geometry, such as random fields, random graphs and related structures, limit theorems, stochastic calculus and
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international environment, and actively shape interdisciplinary theory on sustainable transformations and well-being. The successful candidate will join the Institute for Lifespan Development, Family and Culture
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contribute to the development of a proof of concept obtained at University Côte d’Azur for accessing the content of a metabolomics knowledge graph (KG) with a large language model. It is Python prototype of a
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in the above-mentioned fieldsHead of a design studio and theory seminar, supervision of Master's thesesTeaching urban/territorial design and theory of urbanismAcademic publicationsOrganisation
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: Research in Geometry, with interest in differential geometry, geometric analysis, hyperbolic geometry, higher Teichmüller theory, or related topics Participation in the scientific activities