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- Delft University of Technology (TU Delft)
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- Delft University of Technology (TU Delft); Published yesterday
- Delft University of Technology (TU Delft); yesterday published
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? Join us to develop deep learning techniques for fusing acoustic sensor data with other vehicle sensors for robust multi-modal environment perception. Help shape the future of autonomous driving! Job
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in challenging deep learning at its core? And
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Are you interested in challenging deep learning at its core? And specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision
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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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, and optimum sampling strategies. Proficiency in machine learning, deep learning, and artificial intelligence techniques. Familiarity with clinical applications and workflows. Basic understanding
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with low-data, sparse, or noisy datasets, typical in early-stage drug discovery. Technical skills: Proficiency in Python (required). Practical experience with machine learning or deep learning workflows
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physics and permeability evolution models from µCT data using machine learning and computational tools (PuMA/CHFEM/MOOSE) validated against experimental observations Bridging scales from pore-level
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your PhD, you will gain deep expertise in Generative AI, specification engineering, and empirical software analysis. You will also publish in top venues, collaborate with leading researchers and develop