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systems Additional Information Work Location(s) Number of offers available1Company/InstitutePRISMECountryFranceCityOrléansPostal Code45100Street12 Rue de BloisGeofield Contact City Orléans Website http
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processes, regularity theory of nonlinear degenerate and singular elliptic and parabolic PDEs, free boundary problems, optimal control of free boundary systems with distributed parameters. Current areas
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on the processing of personal data at Humboldt-Universität within the framework of job advertisements can be found on our Website: https://hu.berlin/DSGVO . Please visit our website www.hu-berlin.de/stellenangebote
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] Subject Areas: mathematical modeling, statistics, machine learning, data-driven modeling, dynamical systems, optimization Appl Deadline: 2026/03/31 23:59:59 (posted 2026/02/19) Position Description: Apply
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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of theproject: 1. Initial coordination of the project 2. Optimization of the bed receiver using AI from the data already available. This consists of the operation of the bed under direct and indirect mode, using
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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on the development and analysis of continuous and discrete models in connection with convex and nonconvex optimization problems and monotone inclusion systems. Our ideal candidate already has experience with modern
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promising technology for producing large and complex metal component. Although its potential has been widely demonstrated, significant challenges remain in optimizing the process to ensure the quality
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, surrogate modeling of scientific processes, workflow automation and adaptive simulation pipelines, and performance analysis and optimization. The candidate will also contribute to and help originate research