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algorithms to shape the liveable cities of tomorrow? Job description Human-centred AI techniques, such as Reinforcement Learning from Human Feedback (RLHF), hold great potential for supporting design
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linearization with limited or imperfect models. Learning-enabled control dynamics Embedding optimization and learning algorithms (e.g., SGD, Bayesian updates) into control design and analysis. Attack-tolerant
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optimization methods for run-time network configuration and control. You will design efficient and lightweight learning-based techniques for automated scheduling, network resource allocation, and parameter
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3 Apr 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Design engineering Researcher Profile Leading Researcher (R4) Established
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on practical feedback linearization with limited or imperfect models. Learning-enabled control dynamics Embedding optimization and learning algorithms (e.g., SGD, Bayesian updates) into control design and
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11 Apr 2026 Job Information Organisation/Company AMOLF Research Field Engineering » Design engineering Engineering » Microengineering Physics » Applied physics Physics » Optics Researcher Profile
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23 Mar 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Design engineering Engineering » Systems engineering Environmental science
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into answering counterfactual questions. Using remote sensing multimodal time-series data and Earth foundation model embeddings, you will design and develop causal machine learning models tailored for dynamic
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Development Goals. Your colleagues: A small, international, and close-knit team of five within UNU-MERIT. At the Capacity Development Office (CDO), we design and deliver programmes that help professionals
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innovation with clinical relevance and real-world impact. Postdoctoral Researcher Explainable AI and Foundation Models for CT Imaging Our goal: To develop and validate novel AI methods that enhance