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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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process. This project offers a unique opportunity to work at the intersection of machine learning and control theory. You will develop rigorous theory and scalable computational methods for certifying
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investigate how the strengths of modern machine learning can be combined with the rigorous foundations of control systems theory to create a new generation of intelligent underwater robotic systems
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mechanisms that integrate queueing theory, traffic modelling, machine learning, and network-performance prediction for improving latency, reliability and fairness to support mission‑critical services
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into applications. TRILOGY brings together 11 leading institutions across Europe to train 16 Doctoral Candidates at the forefront of theory and experiment in ultrafast science. The programme offers a unique
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of control systems theory to create a new generation of intelligent underwater robotic systems. The research will focus on developing hybrid learning–control architectures that integrate model-based control
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European estuaries, thereby linking fundamental theory to real-world applications. In the second phase of the project, the research will advance beyond the traditional 2DV framework by incorporating lateral
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, leaving room to pursue the directions that best match your interests and strengths. You will join the Information and Communication Theory Lab (ICT Lab) at TU/e, an international and diverse group focused
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Energy, Physical Resource Theory, Operational Research, or similar areas. Advanced knowledge of written and spoken English is required. You should be able to communicate both within the academic community
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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