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Field
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efficient simulators for continuous and discrete variable systems with noise based on Gaussian/stabilizer decompositions quantum error mitigation and correction for continuous variable systems evaluating and
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. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and
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bridging theoretical physics and theoretical computer science. In the course of this, you will work on implementing efficient simulators for continuous and discrete variable systems with noise based
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excursions. The PhD student will work on analysing the reliability of paleomagnetic records, deriving uncertainty estimates, and building time-dependent models of the paleomagnetic field evolution using a
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methods to tackle challenges in scientific modeling. Affiliations: Technical University of Munich (TUM) & Helmholtz Munich Niki Kilbertus invites applications for a fully funded PhD position. We’re looking
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, biochemists and technicians. The multidisciplinary research in our group covers a wide range of topics from radiobiology, radiation physics and space research to radiation therapy. The radiobiological modelling
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Project (PhD Position) – Quantum-Classical Co-Simulation Framework Development for Neurobiological Systems Your Job: The overarching goal is to implement a code for multiscale quantum mechanics / molecular
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Your Job: The overarching goal is to implement a code for multiscale quantum mechanics / molecular mechanics (QM/MM) molecular dynamics simulations using a Quantum Centric Supercomputing (QSC
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integration of energy systems data and models and apply data science methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science