10 learning PhD positions at Delft University of Technology (TU Delft) in Netherlands
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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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for single-cell and spatial omics Deep learning and representation learning to model cellular states and interactions Explainable AI for biomarker discovery and patient stratification Cross-disease modeling
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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 the adaptation of the Environmental Noise Directive for these new technologies. Your main focus will be to develop machine learning-based drone noise models that will be able to generate an accoustic footprint
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; Develop system architecture and training strategy to enable the FM to learn from heterogeneous MRI data in terms of data source purpose and physical location in the scanner; Develop efficient techniques
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an implementable structural glass window solution, conducting small experiments to determine glass-building properties and/or helping to acquire funding for larger experiments. You will work closely with colleagues
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physical). Solid background in programming and experience with machine learning. Knowledge of participatory design and co-creation methodologies. Ability to learn independently and passion for research
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NExTWORKx, the strategic partnership between the telecom and ICT service provider KPN and Delft University of Technology. Curious to learn more about the project? Feel free to visit our website , where you’ll
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about everyone’s research project and try to help and learn from each other’s problems to boost our scientific and personal growth. We also enjoy many team-building activities and events where you will
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accompanying partner with their job search in the Netherlands. Additional information If you're interested in learning more, please email to Wolf Song y.song@tudelft.nl Application procedure Are you interested