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language models and reinforcement learning for real-time optimization, fault self-recovery, and production scheduling in industrial processes. Publish research results in top-tier international conferences
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diffusion models for synthesis of 5G/6G coverage maps, channel characterization, medical imaging, and RF signal synthesis. Study new reinforcement learning and DQN designs for beam tracking and management in
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and reinforcement. It will build on extensive pavement performance datasets and apply advanced machine learning and statistical methods to generate predictions and assess the effectiveness of different
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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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engineering Researcher Profile Recognised Researcher (R2) Positions PhD Positions Country Poland Application Deadline 7 Dec 2025 - 00:00 (Europe/Brussels) Type of Contract Temporary Job Status Full-time Hours
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oriented institution of higher learning, that is committed to an educational system based on the highest standards of teaching and research in fields related to the sustainable economic development
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School, please visit https://www.tudelft.nl/onderwijs/opleidingen/phd Job requirements We are looking to build a diverse and complementary project team. Applicants should have or expect to receive a PhD in
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of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement learning, and Data-driven modeling and control. The Post-Doctoral associate will be based at NYU Abu Dhabi and will directly
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community. Job requirements You have: A PhD in education sciences, learning sciences, engineering education, or a closely related discipline. Proven expertise or strong interest in educational research design
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of the control of biological movements with applications to neural and behavioural data, including abnormal movements observed in clinical populations. The successful candidate will reinforce and expand