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Description The Unsteady Flow Diagnostics Laboratory (UNFoLD) led by Prof. Karen Mulleners at EPFL in Lausanne is looking for multiple PhD students to join the group in the fall of 2025 or early 2026
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, mathematics, physics, remote sensing and machine learning. Experience and skills · Strong interest in modelling, model-data integration, and remote sensing data analysis. · Knowledge of programming, remote
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interdisciplinary character. The Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
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decision support tools. These mathematical models help battery owners make strategic decisions, such as when to charge and discharge or on which electricity markets to focus. In this PhD trajectory, we
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batteries enter the power system, requires state-of-the-art decision support tools. These mathematical models help battery owners make strategic decisions, such as when to charge and discharge or on which
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
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or earlier. The applicant will be expected to recruit and support multiple graduate students by year three. A competitive startup package including funds for graduate students and equipment will be offered
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interannual variability of spectral signatures in different bands (Planet, Sentinel-3, Sentinel-2, ECOSTRESS, Landsat, SMAP), which will be linked to LUE-WUE and gc information from multiple eddy covariance
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9 Sep 2025 Job Information Organisation/Company CNRS Department Laboratoire d'analyse et d'architecture des systèmes Research Field Engineering Computer science Mathematics Researcher Profile First