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Field
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the development towards this end of efficient, highly parallel software running on commodity hardware. Novel methods to compute the stray field from magnetized material with attention to interface and
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aim to uncover the drivers of pathological remodeling. In parallel, we are interested in the regenerative capacity of vascular tissues and the potential for cellular reprogramming to restore function
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Intelligence, Machine Learning, Data Science, Security and Privacy, Parallel and Distributed Computing, Deep Learning, Internet of Things (IoT), and Algorithms. Successful candidates will hold a joint
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Requisition Id 16562 Overview: The Analytics and AI Methods at Scale (AAIMS) group at the National Center of Computational Science (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking
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optimization, and development of tools suitable for high-performance computing environments. Experience with parallel computing and workload management systems such as SLURM is highly desirable. Model
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implements: Algorithms and computer software for omics-based data sets (high-throughput, massively parallel genomic/proteomic/clinical). Data management and analysis solutions that aid in the storage
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software in high-performance computing (HPC) environments. Experience with parallel and accelerated computing frameworks (e.g., OpenMP, MPI) and familiarity with GPUs and large-scale storage systems. Strong
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: 285643185 Job Type Full-Time Overview The Lead Systems Engineer for High Performance Computing (HPC) and Artificial Intelligence (AI) works as part of the Advanced Systems team within Research Computing
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, or the established work of those within the department. Job Description Primary Duties & Responsibilities: Implements algorithms and computer software for analyzing omics-based data sets (high-throughput, massively
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generation followed by imaging at the Imaging core, 3) RNA functional genomics with methods such as massively parallel reporter assays (MPRAs) followed by sequencing at the Genomics core, 4) experimental