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and modelers to use the optical constants in the analysis of observational data from, e.g., Hubble, Spitzer, JWST. Candidates are expected to be proficient doing data reduction and analysis using Python
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: Strong data analysis skills, including experience working with large climate datasets. Programming experience, particularly in Python, and proficiency with UNIX platforms. Matlab, IDL and/or GrADS use
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networks Advanced understanding of remote sensing principles Experience working with large remote sensing datasets Strong programing skills with a preference for Python and Julia languages Strong record
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computing skills are required, obtained in a Unix/Linux environment, and ideally including Fortran/C++ coding, as well as analysis tools such as Python, IDL Point of Contact Mikeala Eligibility Requirements
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desirable: Earth, Physical, and/or Computing Sciences, Carbon Cycle Science, mathematical modeling, programming in a compiled language like C or FORTRAN95, scripting with python or R. Location: Goddard
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a related field. Preferred skills: Experience in AI, machine vision, image analysis, robotics, autonomous systems, and agricultural sensing. Experience with Python, machine learning or deep learning
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or further their skills in using the Large Fire Simulator, FLAMSTAT, the Forest Inventory and Analysis Datamart, the TreeMap dataset, the FuelMap dataset, ArcGIS Pro, R, and/or Python. Learning Objectives
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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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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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within the past five years, or anticipated to be received by 7/1/2028. Preferred skills: Programming language appropriate for data analysis and visualization, such as Python, Knowledge of acquiring