162 computational-physics-"https:"-"https:"-"https:"-"https:"-"Univ" positions at ETH Zurich
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. Neuromorphic computing and ML deployment on digital and neuromorphic processors TinyML and EdgeAI and ultra-low-power inference for resource-constrained systems Techniques such as quantization, pruning
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apply bioinformatics and statistical genomics approaches to characterize trait-associated sequence variation. We offer two PhD positions at the interface of computational and statistical genomics, and
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novel research programme at the frontier of multimodal AI and ICU clinical cognition. Under the guidance of Prof. Jutzeler, a dedicated postdoctoral researcher, and collaborators, you will have access
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100%, Zurich, fixed-term Human–Computer Interaction in Architecture and Digital Fabrication This fully funded, full-time PhD position spans four years and is embedded within the interdisciplinary
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100%, Basel, fixed-term The Computational Evolution Group, led by Prof. Dr. Tanja Stadler, in the Department of Biosystems Science and Engineering (D-BSSE) at ETH Zürich works at the interface
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. As part of your role, you will: Take technical ownership of spacecraft avionics subsystems, acting as the primary technical authority for onboard computing and data handling within the assigned project
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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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deposition process parameters govern film architecture (e.g., thickness, porosity, roughness, grain/particle connectivity, interfaces, adhesion, and pattern fidelity) and how this architecture ultimately
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We look forward to receiving your online application (English, PDF format), including: Motivation letter (max. 1 page) outlining your qualifications and motivation for this project. Research proposal (max. 3 pages) on "Future of food processing for affordable, nutritious and more sustainable...
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The Mobile Robotics Lab (MRL) at ETH Zürich pushes the limits of robot intelligence. We want to build robots that can safely explore, navigate, and interact with their environments—specifically, how learned perception can drive action in a closed loop and how we can leverage foundation models...