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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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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
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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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Mathematics (Inverse Problems), Computer Science (Machine learning, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of the NXTGen High-tech
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of
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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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are promoting more resource intensive lifestyles under banners of health, safety and pleasance. While the Human-Computer Interaction (HCI) community shaping smart technologies is still coming to terms with its
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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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storage, but their widespread deployment is limited by challenges in energy density, stability, solubility, and cost of electroactive redox compounds. The PhD candidate will develop and apply machine
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from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques to uncover