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research combines inverse problems, numerical mathematics, optimisation, machine learning and imaging physics, with applications ranging from medical and industrial imaging to geophysics. For more
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, solvent-based recycling process for complex plastic waste streams such as multilayer packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process
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postdoctoral appointment in Remote Sensing of the land surface, with a strong interest in the integration of geospatial Artificial Intelligence (AI) and machine learning. Are you enthusiastic about the chance to
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closely related discipline). You have a strong interest in AI/machine learning, data mining, regression analysis, responsible AI, causal inference, and programming (R/Python, SQL). Moreover, you are driven
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packaging and e-waste, while Exergy will develop the digital-twin and machine-learning tools that make the process adaptive and scalable. The research effort will be directed towards the selective recovery in
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imaging. Experience with scientific programming (e.g., MATLAB, Python and/or C++). Excellent analytical and problem-solving skills. Interest in image reconstruction, beamforming, machine learning, and
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resources engineeringEducation LevelMaster Degree or equivalent Skills/Qualifications Experience with hydraulic modelling, optimisation libraries, uncertainty quantification, data science, machine learning
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adaptive resource allocation, AI-driven network orchestration, dynamic beam steering, joint communication and sensing, and cross-layer optimization. Machine learning techniques will be investigated
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following areas: Machine Learning, Deep Learning, Reinforcement Learning, Data Mining; Programming; Parallel programming and High-Performance; Computing; Scientific computing, Numerical methods, and Numerical
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20 Aug 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile