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Field
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good performance in your Master’s studies in Electrical Engineering, Computer Science, Geoinformatics, Energy Systems, or related field Solid programming skills in Python and familiarity with machine
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. Excellent proficiency in spatial and statistical programming (e.g., R, Python, or Google Earth Engine). Proficiency in, and commitment to, version control (e.g., Git), reproducible research practices, and
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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and AI algorithms Solid programming skills in Python and familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience working with geospatial data (e.g., geopandas
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candidate will have a strong background in data analytics, be proficient in a general programming language (like Python) or a statistical package (R), and an appetite for engaging in non-quantitative aspects
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languages: R or Python. Proficiency in Microsoft Office (including Outlook, Word, Excel, PowerPoint). Ability to work independently, but collaboratively on multiple projects. Ability to work strategically
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at least one of the following programming languages: R or Python. Proficiency in Microsoft Office (including Outlook, Word, Excel, PowerPoint). Ability to work independently, but collaboratively on multiple
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computer science or engineering with experience with agricultural systems • Experience handling data from private farms; proficiency with statistical software and programming, GIS/remote sensing, drone imagery
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related field. Demonstrated expertise in spatial analysis & GIS and remote sensing for land/water/agricultural applications. Strong programming skills in Python and/or R (geospatial stacks, data wrangling