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Field
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BatPaC model Understanding of resource recovery technologies, supply chain analysis and upstream and downstream processes Knowledge of Aspen Plus or other chemical process simulation software. Ability
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post-doctoral research associate to simulate amorphous materials and crystallization reactions using atomic-scale simulations. As a post-doc, you will utilize high performance computing and rare event
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physical environments. This position focuses on research at the intersection of computer graphics, generative AI, and robotics, encompassing topics such as generative modeling, reinforcement learning, multi
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for a Postdoctoral Research Associate position in the Physics Simulation Department of the Computational Science and Artificial Intelligence Directorate. The selected candidate will pursue foundational
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 2 hours ago
-, yarn- and weave-scale structure and physics with thermal protection composite-scale performance. Objective: We are seeking proposals to apply and develop simulation techniques to study the role of micro
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. The position is ideal for a candidate passionate about closing the loop between computational simulations and wet-lab experiments. Job Related Minimum Required Education and Experience Requires a Doctoral (Ph.D
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at time of start) PhD or equivalent international degree. Preferred qualifications PhD in physics or astrophysics field. Strong programming skills (e.g., Python) for scientific computing and simulation
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: 280329161 Position: Postdoctoral Researcher in dual-frequency comb spectroscopy at the nanoscale - Copy Description: The Princeton University Department of Chemistry seeks to hire a postdoctoral researcher
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structural models and compute electronic and vibrational properties. Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations
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allow users to input CDR forcing (e.g., alkalinity addition) and produce day-by-day forecasts of CO2 uptake and storage durability. The project combines physics-based modeling, machine learning, and high