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or OpenMP. Experience in heterogeneous programming (i.e., GPU programming) and/or developing, debugging, and profiling massively parallel codes. Experience with using high performance computing (HPC
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 11 days ago
to contribute to innovative projects at the forefront of healthcare delivery improvement, leveraging Large Language Models (LLMs) and clinical data analysis. About the Position Our Postdoctoral Research Program
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research
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to teaching and course development for the Ph.D. in Human Genetics program. Provides research mentoring to postdocs and graduate students. Contributes to development of collaborative grant applications. About
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software for multi-arch environments Development in high-performance computing (HPC) or distributed systems Strong understanding of Linux toolchains, build systems (CMake), and debugging tools Parallel
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software for multi-arch environments Development in high-performance computing (HPC) or distributed systems Strong understanding of Linux toolchains, build systems (CMake), and debugging tools Parallel
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toolchains, build systems (CMake), and debugging tools Parallel computing libraries (MPI, RPC, Mercury, Margo) Experience with HTML and web technologies. Cloud computing platforms and web deployment
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Position Summary Functional Genomics of circular RNAs in Alzheimer's Disease. The Cruchaga Lab, member of the NeuroGenomics and Informatics Center, is recruiting a motivated, creative, self-driven
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Abilities: Experienced in heterogenous computing with GPU accelerators using one of the programming models: CUDA, HIP, SYCL, Kokkos, OpenMP, OpenACC and similar. Familiar with distributed parallel computing
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for massively parallel computers. Experience with quantum many-body methods. Preferred Qualifications: A strong computational science background. Familiarity with coupled-cluster method. Understanding