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Science group addresses this mission through the development of quantum computational methods and software for diverse scientific applications. Major Duties/Responsibilities: Conduct research in
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field completed in the last 5 years Experience in polymer or organic synthesis and characterization methods Preferred Qualifications: Knowledge and expertise in multi-step organic synthesis including
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materials. In this role, you will develop and apply methods that integrate physics‑guided image correction with intelligent (AI/ML‑enabled) data‑acquisition strategies. Key objectives include (1) implementing
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Requisition Id 16254 Overview: Do you have a passion for applying AI methods for accelerating scientific discoveries and an ability to think outside of the box in a collaborative and open
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resources and demonstrated ability in applying numerical techniques to water-energy research. Strong candidates will have advanced knowledge and skills relevant to one or more of the following areas: River
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, Integrity, Teamwork, Safety, and Service Preferred Qualifications: Deep expertise in atomistic and multiscale simulation methods (e.g., MD, enhanced sampling, QM/MM) Experience improving performance and
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programming (C++, MPI, CUDA/HIP/ROCm). Preferred Qualifications: Familiarity with LLVM/MLIR development and multi‑language IR ecosystems. Background in formal methods or automated reasoning. Experience with
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experiments. You will play an integral role in electron microscopy and closely collaborate with other scientists for synthesis, theoretical calculations, and other characterization methods across multiple
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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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Experience with numerical computing using programming languages such as C++, Python, etc. Author or co-author of open literature publications Special Requirements: Applicants cannot have received their Ph.D