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Field
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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research efforts. Key responsibilities for this role include: Initiating, planning, and overseeing research projects Leading the analysis of complex multiomics data, including single-cell and spatial omics
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-omic, multi-context gene regulatory networks (GRNs) from large-scale single-cell datasets. We are pioneers in GRN reconstruction from single-cell multi-omics, including: Causal GRNs from Perturb-seq
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, for example, on elite network data, union data and measures of institutional embeddedness. The Fellow is expected to produce original research work from this data, delivering historical analysis of income
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power system operations, necessitating more complex and adaptive decision-making processes for system operators. While some prototypical power system optimization problems have been adapted for quantum
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learning in neural networks within the ANR-funded MAPLE project, under the supervision of Dr. Bruno Loureiro . Funding is available for two years. Responsibilities Conduct research on the mathematical
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Ph.D. in Geosciences or a related field. Preferred Qualifications: Prior experience in river modeling, river-lake network analysis and biogeochemistry. Demonstrated ability to solve complex differential
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analysis and visualization of typically large and complex information spaces, for example in biochemistry, humanities, or software engineering. Our vision is to attack the big data challenge by a combination
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this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training
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of modeling higher-order relational structures such as hypergraphs and simplicial complexes, which are prevalent in complex biological systems like protein assemblies, signaling pathways, and metabolic networks