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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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process. Together, these innovations aim to make column generation more practical for solving real-world, large-scale optimization problems. These innovations will be tested within a structured software
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. Main tasks and responsibilities: Design soft robotic grippers with embedded sensors Develop and optimize multi-material 3D printing processes Integrate sensors and adaptive control systems Validate
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Job Description Are you interested in putting science in direct benefit of society? We are offering a full PhD fellowship to explore how AI, Mathematical Optimization, and Game Theory can be used
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dynamic community of PhD students and actively supports diversity. We are looking for a motivated applicant with good competences in operation research who wants to gain hands-on experience in cutting-edge
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, synthesis, and characterization of silicone-based foams for innovative healthcare applications. Key tasks will include tailoring the chemistry and processing of silicone polymers to create controlled foam
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Job Description Do you want to contribute to a greener future where state-of-the-art scanning nitrogen vacancy (NV) magnetometry is introduced to visualize buried functional processes in energy
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skills and a keen interest in data-driven research. Your role will be to apply the developed semantic infrastructure to concrete case studies—such as cross-unit scheduling, process optimization