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-of-the-art instrumentation for a broad range of nanoscience research, including nanomaterials synthesis, nanofabrication, imaging/microscopy/characterization, data analytics, and theory/modeling/simulation
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/GC) model. Major Duties/Responsibilities: Lead the planning, design, and construction of the STS conventional facility projects, managing A/E and CM/GC contracts throughout execution. Coordinate cross
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Trust Maturity Model v2.0 DISA STIGs Develop and maintain system documentation, including configuration baselines and operational procedures. Automate administrative tasks using PowerShell or other
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or machine learning potentials (iv) modeling of the solid and aqueous interfaces. Research proposal or concept writing experience. Programming experience for workflow development and scientific computing
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technology; collaborates with members of other data-intensive groups at ORNL to provide cross-discipline approaches; sets, implements, and models standards for performance of work consistent with Environment
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, drawings, bills of materials, specifications, inspection plans, assembly instructions, and test plans/procedures. Utilize SolidWorks 3D CAD to create models and drawings in accordance with ASME Y14.5
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Qualifications: Ideal candidates will possess a background in nuclear engineering. Previous experience using thermal hydraulics models and codes Previous experience using the MOOSE framework. Familiarity with
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Plant Phenotyping Laboratory (https://www.ornl.gov/appl ). Perform phenotypic characterizations of transgenic and genome-edited lines in poplar and other model or bioenergy plants Perform molecular and
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) technologies. Experience with AI/ML concepts and tools (e.g., scikit-learn, TensorFlow, or similar) for basic data analysis and predictive modeling. Experience with relational databases (e.g., PostgreSQL, MySQL
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Substantial programming skills using Python or modern C/C++ Experience with machine learning and deep learning libraries Experience building AI models in platforms such as TensorFlow, Keras, or PyTorch