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Field
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critical data studies and willingness to reflect on data use and circulation. Demonstrable skills in scientific writing and data analysis. Knowledge of GIS and R and/or Python as a tool for data analysis
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complex issues. The ideal 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
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State University of New York University at Albany | Albany, New York | United States | about 2 months ago
weather products primarily using the Python programming language, such as by: using National Weather Service products and models to create forecast graphics and products using observational data like
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planning. Coursework or research experience in road safety, traffic modelling, or transportation planning. Proficiency in working with open data sources for traffic and transit operations using R, Python
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/or text analysis, such as SPSS, Stata, SAS, R, Python, ArcGIS, Atlas.ti, NVivo, GIS, or data visualization tools Demonstrated collaboration skills, with a commitment to supporting an inclusive research
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. Experienced in machine learning and software development in research and production environments. Extensive Python experience, including knowledge of numpy, pandas, Tensorflow and/or Pytorch. Extensive
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also collect soil, water, and plant samples to support environmental research projects. · Data Analysis and Modeling: Employ GIS and image analysis software (e.g., ArcGIS/ENVI) software for remote
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modeling (regional planning, ecological, hydrologic climatic, or wildfire modeling). Experience with scientific software development in C/C++, FORTRAN and/or Python. Experience working with geo-spatial
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Our main research themes are: Life and its Interactions with Dynamic Environments, and Global Landscapes & Climate Change. PhD: 3-4 years full-time; 6-8 years part-time; Thesis of Max 80,000 words MSc (Research): 1-2 years full-time; 2-3 years part-time; MPhil: 2-3 years full-time; 3-4 years...
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and timeframe Different methods will be used to address the Objectives given above. Objective 1: GIS analysis of historic maps and aerial imagery Potentially capture of new UAV imagery Objective 2