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Field
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deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical optimality with computational efficiency. Reinforcement Learning through Stochastic Control. We will
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experimental results What you contribute Enrollment in a full-time degree program at a German university, preferably in the fields of physics, engineering physics, optics, photonics, or quantum communication
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vision research. The position is for 3 years, starting ASAP, focused on ‘Quantum Machine Learning’, with the objective of investigating hybrid classical-quantum and quantum inspired algorithms. The tasks
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2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description 1. Ingesta
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Deadline 21 Sep 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: • Develop optimization algorithms for predictive energy management • Model consumption, renewable generation, storage and CO₂ emissions • Test the
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. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: • Develop real-time optimization algorithms • Model multi-vector energy-water-hydrogen systems • Support the development of digital twins • Test the
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assessment, and hydrographic research. This role translates research algorithms into reliable, documented, and reproducible production software; collaborates with scientists, engineers, students, and external
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mathematics modules at all levels, as well as the PhD programme. Research interests in the Department of Physics currently include particle physics, condensed matter physics and materials science, dynamical
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of underlying 3D scene representations. This requires the designing and developing of specialized computer-generated hologram (CGH) algorithms, modeling the propagation of incoherent light through space