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, machine learning, control theory, or stochastic modeling. Crucially, the ideal candidate must have a proven track record of viewing civil infrastructure through a holistic, interconnected “system of systems
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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absence of large-scale, systematically generated functional measurements needed to adapt, evaluate, and validate these models. You will have the opportunity to work at the intersection of AI, machine
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analyse electrochemical free-energy landscapes and connect elementary-step energetics to catalytic performance apply machine-learning interatomic potentials and microkinetic models where appropriate
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, including AI methodologies and responsible use of large language models (LLMs). Skill development in scientific and technical writing, data engineering, machine learning, and data visualization. Exposure
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, Artificial Intelligence (AI) & Machine-Learning (ML) applications. Good written and oral communication skills Proficiency in power system modelling, advanced control theory (e.g., model-predictive control, etc
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 11 hours ago
. Examples include: determination of high-resolution shape models using shape-from-shading or novel machine-learning methods; studies of high-resolution shape models for geophysical and geological studies
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image analysis, data processing and machine-learning-based modelling. More about the position The main purpose of the fellowship is research training leading to the successful completion of a PhD degree
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at experimentally informed microstructural features. You will combine first-principles modelling and machine-learning approaches to develop predictive simulations of hydrogen behaviour in compositionally complex Fe
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above) grades. You have a strong background in deep learning. Previous experience with robotics, world models, reinforcement learning or other ML-based techniques for robot control is considered a plus