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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi
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written and spoken. Experience with experimental fluid mechanics and computer vision is an advantage. Our offer We offer a stimulating, multidisciplinary research environment within the ETH Domain, with
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Master’s degree in Computer Science, AI, Machine Learning, Mathematics, Electrical Engineering, or a closely related field; or Master’s degree in Medicine (MD) with strong Python skills and some ML
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100%, Zurich, fixed-term The Forest Resources Management Group (FORM) at ETH aims to maximize forest utilities for humans today and in the future. With this vision in mind our research is centered
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reality (XR), machine vision, and human-robot collaboration. Project background The research investigates how interactive computational tools, extended reality (XR), and robotic systems can augment human
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Computational Design Lab and work at the interface of computer vision, computer graphics, hardware, and extended reality. The project is part of ETHAR, a new research initiative at ETH Zürich with a unique focus
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upcoming areas off the beaten paths. Our three main areas of research are machine learning, distributed systems, and theory of networks. Within these three areas, we are currently working on several projects
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through the use of advanced 3D Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to implement physically-based garment
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annotation, and emerging machine-learning and generative methods for spectra or structure proposals. Evaluate and test emerging technologies (hardware and software) in close interaction with collaborators and
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experience with CAD/FEM software Experience in one or more of the following fields is a plus: simulation frameworks (e.g. SOFA, NVIDIA IsaacLab), ROS1/2, machine learning, computer vision Excellent