20 machine-learning PhD positions at Delft University of Technology (TU Delft) in Netherlands
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develop novel graph-based machine learning algorithms for state estimation of energy systems. The scientific challenge is to design a real-time state estimator for an active distribution system considering
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research area. Prior experience working with Neural Radiance Fields or Gaussian Splatting. Prospective applicants should have a strong academic record with a solid background in Machine Learning (Deep
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strong academic record with a solid background in Machine Learning (Deep Learning, generative models, diffusion models). Knowledge in sensor data processing and radaris a plus. Good programming skills
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, computational fluid mechanics, high-performance computing, and physics-informed machine learning. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and uncertainty
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of biomechanical modeling, image segmentation, vision-based motion capture, machine learning, and control systems. Experience with OpenSim model creation and simulation. Keep in mind that this describes
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the power of data and machine learning! Job Description We are seeking a highly motivated PhD candidate to join our research team focused on Collaborative Metadata Management for Large Data Repositories
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based on modern active learning (PhD1) and synthesis (PhD2) technology. Job description You will research the state-of-the-art in AI and apply it to real-world software problems at our industrial partners
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reconstruction and prediction using machine learning models, integrating these model to enhance operational efficiency and safety. Requirements Academic Background: Master’s degree (or equivalent) in Aerospace
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requisites: MSc in engineering and policy, complex systems, data-science, materials science engineering or a related area. Good expertise or strong interest in numerical modeling, machine learning, scientific
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some academic research experience post-Master level. Demonstrable affinity with archival sources. Strong skills in GIS-based research, additional experience with computer vision and machine learning is a