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- University of Amsterdam (UvA); Published yesterday
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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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, intelligent vehicles / robotics, acoustics and signal processing, computer vision. Demonstratable experience in applying Deep Learning, using PyTorch, TensorFlow, JAX on real-world sensor data. Experience with
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apply a Research Through Design (RTD) methodology to further specify the pathways towards these visions with spatial strategies on the middle-long-term (year 2035-2055). This RTD approach should fit
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, recurrent thrombosis, and post-thrombotic syndrome Post-thrombotic syndrome (PTS) is a chronic complication following deep vein thrombosis (DVT), particularly in patients with iliofemoral DVT or recurrent
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Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from
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of Applied Math at the University of Twente has a diverse and vibrant environment for research in Machine Learning and adjoining areas, such as Deep Learning, Mathematical Statistics, Combinatorial
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, mathematical logic or statistical learning theory. For PhD position 2, we appreciate prior experience in implementing deep learning models for graphs and networks. Our offer As a PhD candidate at UT, you will be
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, we appreciate prior experience in implementing deep learning models for graphs and networks. Additional Information Benefits As a PhD candidate at UT, you will be appointed to a full-time position for
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interested in using AI to unravel the mysteries of the brain? Do you want to perform cutting-edge NeuroAI research and leverage deep learning to understand human vision? Then check out the vacancy below and
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Conduct original and novel research in the field of Computer Vision and Machine Learning Develop and analyse novel deep-learning methods to learn for visual representation learning; Publish and present