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to have a strong theoretical and numerical background in one or more of the following fields: Control theory and dynamical systems Theoretical Machine Learning Data science and information theory
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Machine Learning Data science and information theory Network science and multi-agent systems Context: UCLouvain is a comprehensive university offering the opportunity of conducting cross-disciplinary
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resources. Applicants are expected to have a strong theoretical and numerical background in one or more of the following fields: Control theory and dynamical systems Theoretical Machine Learning Data science
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the Computational Biology (CBIO) and Computer Engineering (INGI) units from UCLouvain and will involve other major academic actors. • Hybrid schedule (up to 50% of remote work) • On-site work in the
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-resolution data sets with innovative machine learning methods to create a method that provides an interpretable local estimate of heat, heat stress and health impacts, given the large-scale temperature, local
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drone-borne GPR results (in joint effort with UCLouvain). The expected outcome is a validated algorithm and computer code that combines data-driven propagation operators and full-wave inversion to make
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UCLouvain). The expected outcome is a validated algorithm and computer code that combines data-driven propagation operators and full-wave inversion to make surface and subsurface moisture maps. The training
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will be calibrated with drone-borne GPR results (in joint effort with UCLouvain). The expected outcome is a validated algorithm and computer code that combines data-driven propagation operators and full