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of large-scale genomic and transcriptomic datasets ('big data'), with hands-on experience in high-performance computing (HPC) environments (e.g., command-line interface, scripting in R/Python, use of common
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applications and end user experiences Writing code using programming languages such as C#, C++, Python, Kotlin, Java or Swift Developing and implementing APIs to write XR applications and use OpenXR standards
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scripting languages (e.g. R, Bash, Perl, Python) and with open-source bioinformatics tools. Experience with genome assembly and/or analysis Excellent wet lab and basic molecular biology skills. Be highly
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of the relevant fields. Preferred skills: Previous experience in computational ecology and statistics. R or Python. Statistical analysis tools such as NIMBLE, JAGS or STAN. Familiarity with data processing, quality
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) data sets in R or Python as well as GIS software such as QGIS or ArcGIS Pro. Knowledge of US forest ecosystems and background in analyzing forest structure, stand dynamics, biodiversity, and/or other
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pursuing a bachelor's degree in the one of the relevant fields anticipated to be received by May 31, 2027. Preferred skills: Experience with fire management, landscape ecology, programming (e.g., R or Python
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, Geoscience, Soil Science, Physics, or related fields). Preferred skills: Commitment to contributing to outreach activities and research dissemination. Experience in computer programming (R+, Matlab, Python
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(e.g., command-line interface, scripting in R/Python, use of common bioinformatics software). Strong foundation in experimental design, advanced statistical analysis, and scientific writing. Proven
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improvements focused on vegetative effects on sediment transport. Data processing and analysis will be performed in the MATLAB, Python, Fortran, or R programming languages. Where will I be located? Location
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/statistical skills Experience with statistical analysis software (e.g. R, SAS), GIS software (e.g., ArcGIS, QGis), and programming languages (e.g., R, Python, C++). Experience or interest in science integration