9 machine-learning PhD positions at Delft University of Technology (TU Delft) in Netherlands
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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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, 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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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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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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-deficiency. The hybrid model will combine features of machine learning and statistical models with those of physiological and quantitative genetic models. The PhD candidate will study the available physiology
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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
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optimizations and approaches inspired by machine learning within the framework of cognitive radar; and C) verify the developed approaches with suitable simulations and experimental demonstrations. Specifically
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, combining experimental approaches (single molecule fluorescence and biochemistry) with computational methods. The candidate will obtain single-molecule multiplexing data and validate machine learning