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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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from multiple sources to estimate air quality, along with associated measures of uncertainty. Some traditional models can be relatively restrictive in nature and lack capabilities to deal with large
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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
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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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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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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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steelmaking technologies (e.g., Direct Reduced Iron with hydrogen) and exploring long-term transition pathways through prospective LCA. It will evaluate multiple environmental impact categories, identify