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. Integrate various datasets, such as tree species annotations, climate, and topography, into deep learning algorithms. Test deep learning models (Transformers and CNNs) for optimal accuracy using large
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to revolutionize multiple branches of science by solving problems that cannot be tackled by classical systems. While efficient and large-scale quantum computers are still far from being commercialized, quantum
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institutions, to build a framework for discovering, sharing and executing data and algorithms in a distributed environment. The main technology will be Python, though Scala and Typescript knowledge are a plus
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on algorithms and mathematical proofs, and some on system design and building. Job description The Distributed Computing group at ETH Zurich is looking for a PhD candidate to work on the SNSF Ambizione 2023
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) or neural network-based methods. The level of the targeted problems will require further mathematical and algorithmic developments over the current state of data-driven SSM reduction. The PhD position will
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expertise? Through an Impact Collaboration Programme (ICP) project, you can develop creative ways to work together to ensure that the best available knowledge supports the design of solutions to the complex
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and a computational design and robotic WAAM (wire arc additive manufacturing) fabrication framework for facilitating the reuse of end-of-life steel sections. This will be achieved by tasks related to (i
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using learning-based algorithms Development of a simulation framework for stressor analysis and traffic equilibrium modeling Integration of predictive analytics and multi-agent reinforcement learning
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DIZH understands innovation very broadly and includes all disciplines: artistic, design, natural science, technology, humanities, education and social science.
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elasticity, dissipation, and slender geometry interact to influence crack initiation and growth. Using in-house codes and high-performance computing resources, the candidate will simulate fracture processes