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University of Oklahoma Health Science Center | Oklahoma City, Oklahoma | United States | 29 days ago
parallel recordings (Gong et al. Science, 2015; Beck et al. Scientific Reports 2019); (2) The lab creates fast and accurate algorithms for processing large imaging datasets (Bao et al. Nature Machine
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computational biology, physics and (bio)statistics, biology or medicine. Applicants must have a proven publication record. Prior experience with handling massively parallel sequencing data is considered an
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, and international collaborators. The work will involve large 3D datasets and reproducible computational workflows, including scripted quality control and, when appropriate, parallel processing on high
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-impact work Familiarity with Git and GitHub Competence using Linux-based high-performance parallel computing systems The assessment of applicants will primarily be based on their scientific merits and
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University of Wisconsin - Department of Dermatology | Madison, Wisconsin | United States | 42 minutes ago
CM-AVM patient lesions. Parallel efforts will include generation and application of new conditional alleles to investigate cell-autonomy through Cre-mediated deletion and to model post embryonic
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diffraction in plastically deformed alloys. Implement the framework in parallel simulation codes intended to run on LLNL supercomputers. Design and conduct complex molecular and dislocation dynamic
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Experience with FORTRAN, C/C++, and parallel computing. Experience in theoretical/computational studies of material microstructure evolution involving microelasticity and/or plasticity effects. Experience with
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. AlphaFold-class methods), molecular modeling software such as Rosetta, and GPU-accelerated computing. You will build robust and scalable computational pipelines and drive the project scientifically and
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Experience with FORTRAN, C/C++, and parallel computing. Experience in theoretical/computational studies of material microstructure evolution involving microelasticity and/or plasticity effects. Experience with
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-based surrogate models. Experience with high-performance and parallel computing. Familiarity with digital twins and real-time deployment of predictive models is an advantage. Who we are The two