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University of Massachusetts Medical School | Worcester, Massachusetts | United States | 4 minutes ago
General Summary of the Position Postdoctoral positions in Deep-Learning Omics are available in the Zhou Lab (https://profiles.umassmed.edu/display/20062865 ). The Zhou Lab at UMass Chan Medical
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center, please visit http://csiss.gmu.edu/. George Mason University College of Science (Mason Science) is committed to advancing inclusive excellence and fostering an environment free from discrimination
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months. Where to apply Website https://www.iastro.pt/ia/jobDetails.html?ID=274 Requirements Research FieldAstronomyEducation LevelPhD or equivalent Skills/Qualifications . The call admission requirements
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LevelPhD or equivalent Skills/Qualifications - Excellent knowledge in architecture of quantized and pruned neural networks - Solid programming skills, languages C / C++ / Python - Solid knowledge in
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expertise in analysing complex quantitative and computational data and/or rich qualitative data. • Proficiency or skills to learn a statistical software (e.g., R, Stata, Python). • Interest in contributing
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the application. Required qualifications: Solid insights in marine ecology Programming skills in Fortran, Python and R Demonstrated skills in statistical analyses and modelling Capacity to work with complex data
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(e.g., Python, R, SQL) is an advantage, experience with big data, remote sensing, modelling, or automation of analytical processes is welcome. LanguagesENGLISHLevelGood Research FieldGeographyYears
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programming (e.g., Python) and working with Linux/Unix environments. Solid mathematical/statistical skills. Preferred/desired qualifications Experience in applying for ESA projects, Horizon Europe, and similar
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, deep learning, and statistical modeling Strong programming skills (e.g., Python, R, TensorFlow/PyTorch) Experience handling large-scale ecological, biological, or remote sensing datasets Strong
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particle physics phenomenology -programming in C++ and/or Python -fluent knowledge of English language Welcome: experience in Monte Carlo methods and statistical modeling experience in QCD phenomenology