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Qualifications: PhD and 2+ years of experience in a computational discipline such as Computer Science, Statistics, Biomedical Engineering, or a related field. Experience with multi-modal learning across modalities
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Directorate. In this role, you will lead the development and application of physics-informed data science and machine learning approaches to support nuclear nonproliferation missions. The successful candidate
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strengths in any of these areas — quantitative imaging, modeling/transport science, machine learning, or scientific programming — are encouraged to apply. Major Duties/Responsibilities: Lead energy‑storage
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competing structural phases and the vibrational and electronic structure in materials with defects and disorder. This effort will further seek to implement strategies to leverage machine learning techniques
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Requisition Id 15885 Overview: We are seeking a Postdoctoral Research Associate – Simulation and Machine Learning for Composite Manufacturing who will focus on developing physics-based simulation
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more than 1,000 experiments in the physical, chemical, materials, biological and medical sciences for more than 3,000 visiting scientists. To learn more about Neutron Sciences at ORNL go to: http
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD in Physics, Nuclear
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, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD in Physics, Nuclear
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energy, science, and technology. Leveraging a 75+ year UT–ORNL collaboration, UT-ORII supports convergent research, joint institutes, interdisciplinary PhD programs, and leadership development