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large remote sensing datasets (e.g., Landsat, Sentinel-2, MODIS) and spatial datasets (e.g., FACTs, FTEM, field data) both locally with R/Python and via Google Earth Engine for wild-treatment outcome
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will possess: A strong background in scientific programing Interest in developing open-source data analysis and modeling tools in one of the following languages: Python, Julia, or C . A strong interest
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Programming, C++ Programming Language, Data Integration, Genome Assembly, Genomic Data Analysis, Genomics, Independent Research, Machine Learning, Molecular Biology Techniques, Python (Programming Language
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learning from computer science or related areas and be proficient in Java, C, and Python programming. Familiarity with the source code of major open source machine learning software packages such as Weka
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engineering. · Proficient in programming languages, including Python, R, Julia, etc. · Proficient in database management systems, i.e., MySQL or Microsoft SQL Server. · Proficient in traffic
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, Python (Programming Language), Researching, Results Reporting, Scientific Writing, Work Collaboratively, Working Independently Questions For frequently asked questions about the application process, please
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programming language (R, Python, or Perl) and experience working in Linux and/or high-performance cluster environments. A strong ability to perform analytical reasoning to extract biological insights from data
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not have exceeded two years previous work at the postdoctoral level at start of appointment. Coding experience in a scientific computing language is desirable (e.g., Python, MATLAB, R, IDL, Fortran, etc
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previous work at the postdoctoral level at start of appointment. Coding experience in a scientific computing language is desirable (e.g., Python, MATLAB, R, IDL, Fortran, etc.) The candidate should have an
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not have exceeded two years previous work at the postdoctoral level at start of appointment. Coding experience in a scientific computing language is desirable (e.g., Python, MATLAB, R, IDL, Fortran, etc