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/Responsibilities: Conduct research on deformation mechanisms and mechanical behavior of advanced structural alloys. Perform detailed microstructural characterization using SEM, EBSD, TEM, XRD, and related techniques
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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laboratory experiments, analyze quantitative data, and effectively communicate scientific results through publications and presentations. Major Duties/Responsibilities: Perform molecular genetics, synthetic
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hardware. As part of our team, you will perform research to develop new scalable quantum simulation algorithms, based on multi-linear representation theory, and apply them to real world applications spanning
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. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding. Letters of Recommendation: Please submit
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. You will perform cutting-edge research on theory and modeling of dynamics in condensed matters. Major Duties/Responsibilities: Development of theoretical framework for driven and open quantum systems
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relationships between manufacturing intent, machine behavior, and part performance Optimization of manufacturing processes for improved throughput, reliability, and quality You will contribute to the development
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Oak Ridge National Laboratory, as well as external industry partners. Major Duties/Responsibilities: Understand the processing-microstructure-property relationships in non-ferrous alloy systems. Perform
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(ESTD) at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to perform R&D in the areas of electromagnetic transient (EMT) simulation and software development as
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motivated and talented postdoctoral research associate(s) to join our dynamic team. This role lies at the exciting intersection of High-Performance Computing (HPC) and Artificial Intelligence (AI) at scale