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Eindhoven, and the section for Engineering Design and Product Development of DTU jointly invite applications for a 4-year EuroTech PhD project. Information The aim of this exciting, creative, critical and
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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boundaries of system-level modelling, analysis, design, exploration and synthesis beyond the current state-of-the-art? Or are you curious to learn more about the application of AI for system design? We
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Vacancies PhD Position on Designing and Managing Digital Work for Inclusion Key takeaways This fully-funded, 4-year PhD research position is part of the project "Don't Forget the Forgotten! Towards
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applicants should have a strong academic record with a solid background in Machine Learning. Knowledge of Vision-Language-Action models and Novel View Synthesis techniques is a strong plus. Good programming
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to state-of-the art AI/machine-learning, from modelling to measuring emissions and climate effects, noise and noise propagation. Job requirements The PhD position is funded by the Horizon-Europe TUNED
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, silicon-proven AI/ML accelerator for transmitter error correction (digital predistortion/calibration). Your work will sit at the intersection of machine learning, DSP, and digital IC design, and you will
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sciences, law, and philosophy. Four WPs address citizen-empowerment-scenarios (CES) in healthcare, mobility, public governance, and healthy living. Each PhD position is embedded in one work package and
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. Methodological Approach Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering