90 machine-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation;" positions at ETH Zurich
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Biology, Computer Graphics, Computer Vision, Control Systems, Deep Learning, Digital Humans, Earth Observation, Educational Technology, Efficient AI, Explainable AI, Haptics, Human-Computer Interaction
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-aware AI Interfaces such as SPI, I2C, UART, CAN, USB, Ethernet, MIPI, or similar Use of oscilloscopes, logic analyzers, power analyzers, and hardware debugging tools Deployment and optimization of machine
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. Our current projects involve large-scale web and text analysis, as well as computer vision and visual data analysis. Applicants may have experience in one or both areas described below. You do not need
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10%-30%, Zurich, fixed-term The Digital Character AI team at ETH Zurich's Computer Graphics Laboratory is looking for a Student Research Assistant to support the development of our interactive AI
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quantification, from classical optimisation and Bayesian inference to physics-informed neural networks (PINNs) and other machine-learning approaches build and extend our simulation environment, with a focus on
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The Computer Security Group is a research group in the Department of Information Technology and Electrical Engineering at ETH Zürich. We are interested in a variety of hot topics in the area of
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strong background in machine learning, computer vision, or 3D point cloud processing, as well as in probabilistic modelling and Bayesian inference Very good programming skills, preferably in Python
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processing, machine learning, and human-computer interaction. The goal of this PhD is to develop neuromotor interfaces for dexterous robot teleoperation using two sensing modalities: 1) surface
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dynamics (MD) simulations including enhanced sampling techniques as well as machine learning. Profile Applicants should hold a M.Sc. in computational chemistry, chemistry, biochemistry, or physics
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can significantly improve the treatment and outcome of oncological patients. Project background You will contribute to the design and implementation of machine-learning-based sparse 3D image