163 computational-physics-"https:"-"https:"-"https:"-"https:"-"U.S" positions at ETH Zurich
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, Switzerland [map ] Subject Areas: Computer Science / Distributed Systems and Networking , Networking , Networking and distributed systems Appl Deadline: 2026/01/08 11:59PM (posted 2025/11/10, listed until
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component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
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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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the institution teams. Profile Required qualifications and skills: Master degree in computer sciences, natural sciences, or equivalent with demonstrated expertise or qualifications (e.g., physics, geography
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80%-100%, Zurich, fixed-term We are seeking a talented Research Engineer with strong expertise in Computer Graphics, physically-based simulation, and high-performance implementation. In this role
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molecular-scale continuum description of inhomogeneous systems – in process design and, therefore, to fuse the scales from molecules to processes. To overcome the computational challenge of applying molecular
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the power of both classical and quantum computing resources? How can we exploit or take inspiration from quantum physics to develop cutting-edge machine learning? Your work will encompass a diverse array of
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100%, Zurich, fixed-term The Computational Design Lab is an interdisciplinary research group at ETH Zurich, led by Prof. Dr. Bernd Bickel . We develop novel algorithms and next-generation
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agreement. We develop computational methods to accelerate materials discovery through defect engineering, with a focus on extreme environments. Application areas include fusion reactors, hydrogen systems, and
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cell biology, and systems-level quantitative biology. The project aims to uncover how mechanical properties, forces, and physical phenotypes integrate with molecular networks to regulate the function