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Requisition Id 16127 Overview: We are seeking a Postdoctoral Research Associate who will develop and apply electronic structure theory approaches to examine the fundamental properties of a range
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crystal material’s growth and characterization. You will perform cutting-edge research on theory and modeling of dynamics in condensed matter. Major Duties/Responsibilities: Development of theoretical
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carlo), as well as experience in developing and/or applying advanced AI/ML methods to accelerate materials discovery. The project will involve integrating such theory-informed AI-models for creating
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eigenvalue problems, and large-scale graph analysis). Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting
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minimum of five years of relevant experience, beyond Ph.D. Demonstrated research experience in the applications of graph-theoretic analysis, probabilistic approaches to complex systems, time-series analysis
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machine learning, deep learning, foundation models, agentic AI systems, graph neural networks, and knowledge‑graph–based reasoning. Familiarity with integrating AI into scientific workflows at scale
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classification policies, laws, and statutes. Advanced knowledge of a wide range of principles, theories, professional competencies & application techniques of discipline, related disciplines, and organization
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, or graph-based encodings in materials and molecular AI. Familiarity with frameworks for automated and reproducible workflows. Knowledge of governing regulations around privacy (e.g., HIPAA, ITAR), including
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, a strong emphasis in delighting customer and end-user needs. Preferred Qualifications: Active DOE Q clearance. Understanding of multidimensional and tabular modelling, vector databases, Graph DB
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storage and analysis solutions (e.g., key-value stores, object or document storage, graph analytics systems) deployed on HPC computational and storage systems. Co-authorship of peer-reviewed publications