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for molecular dynamics (MD), slashing computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with
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the Texas Children's Cancer Center. The project aims to develop and test novel CAR-redirected immunotherapy for pediatric solid tumors. In particular, we want to design and test a regulated PRDM1 knockdown in
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an exciting opportunity to work at the intersection of geoscience and advanced machine learning. The associate will collaborate primarily with Professor Qian Yuan, focusing on integrating state-of-the-art
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measurements from real projects, statistically analyse them, and conduct experiments with modern machine learning techniques and generative AI. A strong background in software engineering as well as some
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 24 days ago
neoclassical tearing modes in metal-wall scenarios; support the creation and validation of machine learning (ML) and hybrid physics + ML models to monitor and control the proximity to stability boundaries
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Mattelaer, Christophe Ringeval). Research activities in include SM and BSM aspects of collider physics (LHC and future colliders, simulation tools, machine learning, effective field theories, amplitude
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University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities
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SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
dynamics, quantum mechanical simulations, and machine learning. Proficiency in programming languages and computational software’s. Strong motivation and passion for research in the field of sustainable
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valued. · Knowledge of chemical reactions and how to model them through computer simulations is highly valued. · Knowledge of classical molecular dynamics, including Machine Learning Interatomic Potentials
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pandemic risk policy and practice. The PDRA will drive a research project within the centre focussed on the application of machine learning and bioinformatics approaches to the prediction of pandemic risks