1,149 parallel-computing-numerical-methods Postdoctoral positions in computer-science
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 4 days ago
Job Offer from September 17, 2026 The “Computational Relativistic Astrophysics" division at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute; AEI) in Potsdam, led by
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. Knowledge of applications of quantum computers to many-body physics problems (e.g., quantum simulation algorithms, hybrid quantum optimisation methods). Other Valued Skills Experience in supervising Master or
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key findings in peer-reviewed journals in a timely manner. Collaborate within a multi-disciplinary research environment consisting of computational scientists, experimentalists, and engineers conducting
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Responsibilities Lead photonic integrated circuit (PIC) design and simulation using commercial tools. Contribute to novel photonic computing architectures including optical in-memory and
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- 21:59 (UTC) Country Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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understanding of data quality, reproducibility and robust analytical practice. Experience of SQL, cloud-based or high-performance computing environments, and Bayesian methods would also be valuable. Beyond
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modelling and partial differential equations; • an understanding of Carleman linearisation approaches and/or the Koopman–von Neumann formulation; • the ability to develop and analyse numerical methods
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curious to deliver work that matters, your journey starts here! The Department of Electrical and Computer Engineering (ECE) ranks among the best in the country. Our research programs are at the forefront
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associated with shellfish culture. Responsibilities will include management of a breeding program for hard clams, and independent research evaluating the environmental stressors influencing shellfish
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following