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capabilities of the existing C++ codebase Applying the framework to morphogenetic problems using real imaging data Conducting large-scale simulations on ETH's HPC infrastructure Performing model calibration
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to engineer human cells and develop advanced gene and cell therapies targeting cancer, as well as metabolic, neurodegenerative, autoimmune and infectious diseases. For more information, please consult our
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project “eDIAMOND: Efficient Distributed Intelligent Applications in Mobile-Network Dynamics” . The eDIAMOND project aims at developing new methods and systems for decentralized and distributed data-driven
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learning (RL), such as (but not limited to) Theory of online learning, reinforcement learning, and data-driven control Learning in games, and multi-agent RL RLHF and alignment in LLMs Representation learning
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17.09.2025 | Departement Architektur Data Science Expert 100%, Zurich, fixed-term 17.09.2025 | Scientific IT Services, ETH IT Services