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team of scientists to develop in situ monitoring technologies for DED-based AM processes. Design, integrate, and deploy multi modal sensor systems (including but not limited to optical, thermal, acoustic
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Requisition Id 15358 Overview: Oak Ridge National Laboratory (ORNL) is seeking an ambitious postdoctoral scientist with keen interest in artificial intelligence (AI) / machine learning (ML) and
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: Development of new protocols to control coherent spin dynamics for optically accessible spin defects. Enable new spin-based quantum sensing protocols in low temperature and high field environments. Maintain and
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computational mesh generation. In this role, you will apply your software engineering skills to develop and validate computational results that support large-scale, physics-based simulations across a variety of
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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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out experiments exploring the dynamics of high-intensity beams in the SNS ring. This project will explore a unique space charge mitigation technique based on coupled optics and phase space painting
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CPU and GPU based HPC systems. Exploration of the capabilities of DPU/IPU SmartNICs to support network security isolation, platform level root-of-trust, and secure platform management/partitioning
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include: (1) understanding dynamics in quantum materials; (2) investigating thermal transport, phase stability, and thermomechanical response through combined neutron-based measurements and complementary
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL
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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