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designing control systems that offer guarantees of safety and constraint satisfaction. The project will research the theory and computation of invariant sets, and their application to new control problems
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Matter Theory , Quantum Control , Quantum criticality and phase transitions , Quantum Devices and Sensing , Quantum Dynamics , Quantum error correction , Quantum Field Theory , quantum gravity , Quantum
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theory, modeling, and AI-assisted optimization activities within the consortium. Reporting and dissemination of the results. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail=1074
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position as Senior Lecturer. Optimization, machine learning, and control theory together form a central toolbox for understanding, analyzing, and controlling complex systems. These fields span deep
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, fully-funded PhD student focused on control, optimization, game theory, and embodied intelligence in robotics and autonomous systems. This is a unique opportunity to work on a project combining cutting
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: Postdoctoral Position Location: Shanghai, Shanghai 200438, China [map ] Subject Area: Physics / quantum information theory and atomic experimental physics Appl Deadline: 2026/04/11 04:59 AM UnitedKingdomTime
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Outreach , Plasma Physics , QCD , Quantum chaos and thermalization , Quantum Computation , Quantum Computing , Quantum Condensed Matter Theory , Quantum Control , Quantum Devices and Sensing , Quantum
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Università degli Studi di Roma Tor Vergata - Dipartimento di Studi letterari filosofici e di storia dell'arte | Italy | 1 day ago
of the theory of categories and of the relation between science and philosophy in classical Greek thought. Such research should consist at least partly in the collation of manuscripts and the evaluation
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non-relativistic holographic frameworks. The project focuses on establishing and using controllable limits of string theory and holography—particularly non-Lorentzian (e.g. Galilean/Newton–Cartan and
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://cavecore.eu/ Your Research Project (DC4) You will work at the intersection of machine learning, control theory, and autonomous multi-agent systems to develop hybrid learning-based control strategies