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Field
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will include development of algorithms for heterogeneous computing architectures and implementation of AI/ML in a real-time environment. The candidate will also have the opportunity to conduct
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artificial intelligence, advanced battery manufacturing, battery prognostics, and battery recycling. The successful candidate is expected to develop rigorous modeling, computational, and/or experimental
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systems, from the physical fabrication of flexible printed circuit boards (FPCBs) to the implementation of machine learning algorithms for real-time signal analysis. The postdoc will collaborate in a
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Computing Methods for Physical Sciences Section in CSED. The MsM group is focused on delivering multiscale, multi-fidelity computational models and systems using algorithms and analytics for materials and
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algorithms at scale on ORNL's computational resources, including the Frontier supercomputer, addressing critical challenges in science and engineering. Communicate and coordinate experimental results with
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the molecular biology of aging and neurodegenerative diseases. Engage in the development and testing/validation of new algorithms and their applications to transcriptomic, epigenomic, genetic, and proteomic data
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help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
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algorithm design skills Expertise on ML tools for chemistry, in particular, generative AI Experience with Python, ML, and AI for chemical applications Job Description: A Post-doctoral Associate in Theoretical
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of Virginia (UVA) School of Medicine is seeking to fill Postdoctoral Researcher positions in computational biology and machine learning. The lab develops modern machine learning, generative modeling, and
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) computer vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial