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: Ph.D. in Computer Science, Computer Engineering, or a field closely related to the job duties of this position. Demonstrated research in one or more areas of HPC or AI (e.g., large-scale training
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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly
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computational and experimental campaigns, running in distributed large-scale advanced computing environments. The group also delivers AI-ready and FAIR scientific data, together with the orchestration, provenance
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documentation practices consistent with group and division goals, policies, procedures, and strategy. Plan and manage medium-to-large configuration-control projects associated with facility construction
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, Python or R Experience in manipulating and analyzing large observation data or model outputs Working knowledge of terrestrial biogeochemistry and nutrient-cycling processes Strong communication skills
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, Python or R Experience in manipulating and analyzing large observation data or model outputs Working knowledge of terrestrial biogeochemistry and nutrient-cycling processes Strong communication skills
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workflows. The successful candidate will develop novel AI methods that integrate scientific knowledge, simulation, experimental data, and large-scale computing to achieve measurable AI advantage in scientific
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, orchestrating large-scale investments and partnerships, and positioning ORNL as the national leader in geospatial HPC, data infrastructure, and emerging computing paradigms (edge compute, neuromorphic, quantum
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such as setup, sample preparation, routine measurements, and recording data. This position supports a large, shared laboratory space used by physicists, uranium chemists, and materials scientists. The ideal
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, root imaging) with biogeochemical, microbial, or environmental sensor data. Experience analyzing large datasets in reproducible formats (R, etc.) Demonstrated interdisciplinary and systems-level approach