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Field
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systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents for autonomous vehicles or robots operating in dynamic
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bridge the fields of Generative AI, Recommendation System, Labor Economics/Organizational Science, and Social Simulation Platform. The key focus areas of this project include: 1. Agentic Career
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
system and its components. ISSM is a modular C++ codebase with MATLAB and Python interfaces, designed to simulate Cryosphere, Solid Earth, and Sea Level processes, either in coupled or standalone
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and fine-tune LLM Agents for hypothesis generation and protocol suggestions. Design and manage a structured, FAIR-compliant knowledge base for materials discovery. Contribute to the development and
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and integrate emerging AI techniques (e.g., agentic workflows, LLMs) into scientific problems, ensuring methods effectively solve real domain challenges. Advanced Model Development: Design and debug
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reinforcement learning Experience with high-performance computing, physics-based simulations, and multimodal data workflows Demonstrated ability to train and deploy AI/ML models using simulated and experimental
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workflows, and immersive or experimental interfaces Integrate LLM-based and agentic AI systems with scientific visualization frameworks, in situ pipelines, and data analysis workflows Prototype and evaluate
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Postdoctoral Appointee - Investigation of Electrocatalytic Interfaces with Advanced X-ray Microscopy
part of the DOE–BES initiative Integrated Scientific Agentic AI for Catalysis (ISAAC) , a multi-facility collaboration integrating experimental modalities and simulations to enable an orchestrating
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workflows, including adaptive, automated, or agent-based (agentic) workflows that integrate simulation, data analysis, and/or machine learning. Experience with computational workflows on large-scale HPC
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knowledge representation • Agent-based and simulation modeling • AI/ML, foundation models, causal inference, and predictive analytics • Human factors, behavior science, and patient-centered design • Advanced