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(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical
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Polytechnique de Paris. The group conducts research at the intersection of statistical learning, machine learning, and data science, with a strong focus on structured data, representation learning, and
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)chemistry and expertise in MD simulations, quantum chemistry or machine learning. Knowledge of biosystems, analysis skills (Python), scripting skills (bash and/or Python) and machine learning are assets
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to work with veterans and military-connected students to enrich the Center of Excellence for Veteran Student Success. To serve as a single point of contact to coordinate comprehensive support services
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 5 days ago
day-to-day use Good knowledge of some 3D vizualisation and GUI libraries (for example OpenGL, ImgUI, Magnum, QT, ...) If possible, basics in robotics (kinematic, etc.) Basics in machine learning Open
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Applications: Microsoft Excel, Microsoft Word, Microsoft Outlook Required Other Computer Applications: Required Additional Knowledge, Skills and Abilities: Demonstrate organizational skills with ability to work
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Functional Theory (DFT), machine-learned force fields (MLFF), graph neural networks (GNNs), or large language models (LLMs). Extensive Knowledge In: • First-principles atomistic simulations with packages
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1668, as amended); master’s degree in the field of Social Sciences, in the discipline of Security Science; knowledge, skills, and experience necessary to teach subjects related to crisis management
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1668, as amended); master’s degree in the field of Social Sciences, in the discipline of Security Science; knowledge, skills, and experience necessary to teach subjects related to defence and security
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 11 hours ago
-PULSE addresses a key open question in responsible AI: can we design practical machine learning systems that satisfy strong privacy guarantees [1] and fairness [2] constraints simultaneously, without