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data-model integration, leveraging the U.S. Department of Energy’s (DOE) Leadership-Class Computing Facilities to advance predictive understanding of complex environmental systems. Major Duties
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high-quality receptor candidates within the specific functional and structural constraints of our platform. You will work directly with modern protein-design and structure-prediction methods, build and
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mathematical foundations needed to make deep operators reliable, robust, and applicable for control of complex engineering systems. In this PhD project, you will investigate how operator-learning models can
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models can predict the performance of marketing content before it is published. Research at the Center builds on the group's track record in data science, conversational AI, and marketing analytics and on
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antigens presented by MHC molecules. This curiosity-driven project develops cutting-edge AI technology for 3D TCR–pMHC modeling to improve neoantigen identification, TCR specificity prediction, and TCR
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provide meaningful explanations of their predictions to downstream users. A central aim of this project is to investigate how Vision-Language Models (VLMs), Multimodal Large Language Models (MLLMs), and
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management. Artificial Intelligence & Machine Learning: Predictive risk modeling for falls, hospitalization, and cognitive decline; Natural Language Processing (NLP) for remote cognitive assessment; image
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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observations/models and from models of social dynamics. Motivating aims include the discovery and analysis of hidden large-scale patterns in data/models, elucidating mechanisms underlying the emergence
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 12 days ago
offers hands-on experience with operational satellite retrieval algorithms, physics-based forward modeling, and mission-scale validation practice, complementing the participant's background and advancing