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candidate will be to use a combination of CUDA, Python and C++ programming to develop CADD tools which will curate the human proteome, upgrade the group’s MoPBS software, develop new GPU enabled pharmacophore
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molecules? If so, read on. Project brief overview You will develop CUDA code to flood binding sites with fragments, minimise their positions and map out pharmacophores similar to my previous MoPBS paper. You
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 12 days ago
: 265566 Vacancy ID: PDS003971 Position Summary/Description: The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https
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Posting Number R260058 Posting Link https://www.ubjobs.buffalo.edu/postings/61964 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting
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, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized knowledge of Neural Rendering (NeRF/3DGS) or Satellite Photogrammetry. Demonstrated
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-field code, written in the Cuda C language and parallelized on a single GPU (Graphical Processor Unit). A parallelization on multiple GPUs would be a welcome development during the thesis. Where to apply
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
/Description: The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https://www.med.unc.edu/pharm/directory/yinglong-miao/) is
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implementing novel and innovative tools, technologies and approaches to fundamental problems in systems and circuit-level neuroscience. For more information about the lab check out: https
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, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/, https://gen3.org/, https
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, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/, https://gen3.org/, https