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such as additive manufacturing, quantum material design, scientific data reconstruction, for material discovery, inverse methods, complex optimization, population and evolutionary dynamics, cyber security
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of conduct, and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity Basic Qualifications: Ph.D. in mathematics, engineering, data/computational science
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/Responsibilities: Provide engineering support for Cooling Systems equipment and projects. Perform hydraulic analysis using computational fluid dynamics (CFD) software to understand performance limitations in
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through this early-career position primarily located at ORNL and with a Joint-Research Faculty (JFO) appointment at UT. As an integral part of the team, you will engage in a dynamic blend of activities
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understanding of core networking concepts such as TCP/IP, UDP, DHCP, static/dynamic IP addressing Hands on laboratory experience performing testing and analysis is required. Good oral and written communication
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) characterizing pellet fueling dynamics using multiple observables, 2) measuring and predicting the dynamic and cumulative impact on long-pulse particle balance and plasma performance, and 3) developing real-time
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dynamics, earthquakes). Experience with physics-informed neural networks or other physics-based machine learning approaches. Knowledge of uncertainty quantification and interpretation in geophysical modeling
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research. Strong written and oral communication skills. The ability to work in a dynamic, team environment. Preferred Qualifications: Experience working with spatio-temporal datasets, remote sensing imagery
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). Research will focus on dynamic and out-of-equilibrium signatures of emergent physics that are observable in both materials experiments and quantum simulations. Active collaborations with experimental and
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, and collaborate across diverse teams. Advanced planning and problem-solving capabilities, particularly in dynamic or compliance-driven settings. Preferred Qualifications: MS degree in computer science