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equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications A Ph.D. in nuclear or health sciences (such as health physics
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physics, fusion research, life sciences, and materials science. Furthermore, these efforts to enhance data readiness for AI workflows may play a significant role in contributing to the goals of the 2025
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Resources, Engineering, Physics, Environmental Science, or related discipline completed within the last 5 years. Preferred Qualifications: Strong candidates will have depth in at least one and breadth across
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by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in physics or a related field completed within the last 5 years
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. Research will involve growth of single crystals and measurements to understand their structural and physical properties including magnetism and thermal transport, as well as helping to identify new magnetic
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. Focus will largely be in developing and deploying such AI/ML algorithms, closely collaborating with theorists and experimentalists to realize physics- models and/or physics-aware ML-models that can bridge
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iterative solvers. Successful applications will work in applications related to gas dynamics, plasma physics, and radiation transport. The position comes with a travel allowance and access to advanced
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Engineering, Nuclear Engineering, Mechanical Engineering, Physics, or a closely related field completed within the last 5 years Demonstrated experience with advanced materials characterization equipment and/or
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nexus, data centers, and water & wastewater sector. You will work independently and with senior technical staff toward collecting data for all steps in development of manufacturing process flow sheets
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methods to work with a team of scientists in CSD to model chemical reactions important to determine the longevity of amorphous materials. That mechanistic information will be incorporated into process-based