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theoretical and computational research on dynamic game theory and multi-agent optimization for uncertain systems. By building on tools from distributed optimization, convex-monotone game theory, and hybrid
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. As a PhD researcher, you will unravel the atomic-scale mechanisms of hydrogen embrittlement in compositionally complex recycled steels, using density functional theory and machine-learned interatomic
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of the defining challenges of the coming decade, and it is exactly where this PhD sits. At TU/e you will join the Information and Communication Theory Lab, a group with a long track record in classical coding and
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of probabilistic and extremal combinatorics, structural graph theory and algorithms. We study problems on discrete structures such as graphs, permutations, posets or set systems using probabilistic, structural and
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Ever wondered what keeps your data flawless, and secret, as it travels through an optical fibre, even against the quantum computers on the horizon? The answer is error-correcting codes: clever maths
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is exactly where this PhD sits. At TU/e you will join the Information and Communication Theory Lab, a group with a long track record in classical coding and information theory: designing and analysing
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Creating superpositions of massive objects with a superconducting qubit: Can we test if gravity is quantum? Job description The radical theory of quantum mechanics is known to describe the fundamental
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traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where possible. This innovative new approach enables more efficient and
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traffic flow theory and simulation. You are a machine learning enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present and communicate your
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coupled-cluster (EOM-CC) theory with periodic DFT (pbcEOM-CC). To quantify spin-phonon couplings of spins on surfaces—the bottleneck to modeling spin relaxation—we will develop a new approach using pbcEOM