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identification and machine learning. The key challenge is striking a balance between, on the one hand, modelling the physical, dynamic and nonlinear behavior of the components with sufficient physical accuracy
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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challenges, creating synergy and fostering new collaborations. For example, one project might involve developing machine learning models to analyse complex neuroimaging data. Another could focus
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, both within UM and with external partners. Teach at bachelor’s and master’s level in AI, climate data, machine learning and related topics into your courses. Supervise and mentor PhD candidates, postdocs
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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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Technology Enabling Advanced Drone- Facilitated Active Support Tactics for Military and First Responder Operations.” You will be a member of the Human-Robot Collaboration Lab and Learning & Autonomous Control
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hold an MSc degree in environmental science or ecology, with a proven expertise in data analysis, organizing and handling. Expertise in machine learning is a plus. A sound command of the English language
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of what microscopes can achieve. You will create and apply sophisticated algorithms, physics-based simulations, and machine learning models to process complex data from our cutting-edge imaging systems
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theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be opportunities to present at leading
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goal is to apply cutting-edge neuro-AI knowledge to various scientific challenges, creating synergy and fostering new collaborations. For example, one project might involve developing machine learning