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Requisition Id 15603 Overview: The National Center for Computational Sciences (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral research associate in the area of HPC
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research career, with responsibilities including leading innovative research studies, ethically collecting and analyzing multi-modality assessment data, preparing research findings for publication in peer
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Center for Advancement of Blood Cancer Therapies (CABCT) (https://icahn.mssm.edu/research/cabct ). The successful candidate will work on projects involving human induced pluripotent stem cells (iPSCs) and
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challenges. We are deeply committed to recruiting and retaining a talented workforce that embraces our core values of Respect, Excellence, Leadership, Loyalty, Integrity, and Service, by offering competitive
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associated with the center on Geo-processes in Mineral Carbon Storage (GMCS), funded through the Energy Frontier Research Centers by the Office of Basic Energy Sciences, US Department of Energy. The main
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interdisciplinary teams. Preferred Knowledge, Skills, and Abilities: Experience scaling machine learning training and/or inference on multi-node HPC systems. History of implementing, adapting, or optimizing machine
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research career, with responsibilities including leading innovative research studies, ethically collecting and analyzing multi-modality assessment data, preparing research findings for publication in peer
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to benchmark its performance. This position offers a unique opportunity to work on a multi-disciplinary project with a team of scientists and engineers and experts in commercialization and translational research
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stress-induced molecular & electrophysiological remodeling in the development of cardiac arrhythmia and heart failure as well as ischemic stroke-caused brain injury; collects and analyzes data for research
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the relationship between technology and society. The priority areas of our center include (1) AI, Data Science and Society, (2) Privacy and Security, and (3) Platforms and Digital Infrastructure. CITP tightly