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10%-30%, Zurich, fixed-term We are looking for motivated student research assistants to join our project “Adaptive Physics-Informed Neural Operators with Reduced-Order Modeling for Complex Dynamical
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100%, Basel, fixed-term A World-Class Research Environment at the Nexus of Biology, Engineering, and Physical Sciences The Biotechnology and Bioengineering group led by Prof. Dr. Martin Fussenegger
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100%, Basel, fixed-term A World-Class Research Environment at the Nexus of Biology, Engineering, and Physical Sciences The Biotechnology and Bioengineering group led by Prof. Dr. Martin Fussenegger
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The current era of artificial intelligence is predominantly driven by advances in computational power and infrastructure. As models scale to unprecedented sizes, their capabilities are enhanced
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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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of Computational Fluid Dynamics CFD environment and simulations including: - Computation of the microwave field, Coupling of the microwave field with the plasma - Computation of elementary ionization, recombination
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models Lead the design and implementation of innovative methods, which could include but are not limited to: Kriging surrogate, Polynomial Chaos Expansion (PCE), and Physics-Informed Neural Networks (PINNs
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work closely with Professor Platt, guide the group’s computational research, contribute to ongoing projects, and pursue independent research directions aligned with the laboratory’s goals. Project
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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 frontend development of our
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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