2,010 parallel-and-distributed-computing "CERN" Postdoctoral positions in United States
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to this topic, and to explore multiple lines of research in parallel. Most projects employ a combination of bacterial genetics, high throughput genetic screens, biochemistry, ribosome profiling (ribo-seq
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, multispectral and infrared imaging, spectroscopy, image processing, computational analysis, and clinical investigation to develop technologies that can improve diagnostic accuracy and reduce disparities in care
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Familiarity with brain imaging analysis acquisition Knowledge of multivariate statistics and/or digital signal processing Proficiency in Python. Parallel computing processing experience is highly appreciated
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in C++/Java/Fortran 90, Python/MATLAB, and MPI-based parallel computing Strong publication record as first author in peer-reviewed journals Preferred qualifications Experience with 3D conjugate heat
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modeling. This position offers a vibrant research environment with access to world-class high-performance computing clusters and opportunities to collaborate broadly across the departments of Physics
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to three publications and three professional references to be contacted only with the approval of candidates. This part-time position is being offered in conjunction with a parallel part-time clinical staff
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experiment or another collider-based high-energy physics experiment Experience with silicon detectors, Trigger/DAQ systems, or detector operations Experience in software and computing, including distributed
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 21 days ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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Details Title Open Postdoc Position – Rowland Institute School Faculty of Arts and Sciences Department/Area Optical microscopy Position Description The brain computes through distributed neural
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implementation science, and leveraging computational innovation, the lab examines these relationships across exposures, tissue types, life stages, and populations to identify opportunities for prevention and early