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Google Earth Engin, R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. Demonstrated record of publishing
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resources/energy, and/or vibrant businesses and places. As such, the preferred fields are JEL categories Q (Agricultural and Natural Resource Economics…) and R (Urban, Rural, Regional…). Essential duties and
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data, database, and/or data lake integration (e.g. Kafka, Apache Spark, Minio, Apache Hive). Knowledge of Linux kernel internals, and kernel modules. Strong scripting abilities in Python, R, and/or bash
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Google Earth Engin, R, Python, and STAN (e.g., deep learning, Bayesian regression models, spatial analyses), and running analyses on a high-performance computing cluster. Demonstrated record of publishing
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of experience in university-wide data gathering and analysis Experience with data base management and analysis Experience with Excel/Google Sheets and statistical software packages (e.g., SPSS, SAS, R) Excellent
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data visualization tools, especially R; Experience with object-oriented programming languages such as Python; Experience supporting experiential and service learning courses; Experience with Adobe
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Python, R, and/or bash. Familiarity with version control using Git. Demonstrated skills automating or optimizing software, code, and/or processes. Experience maintaining the stability and security of Linux
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to offer. Qualifications: Required: PhD in ecology by start date Experience in plant phenology, biogeography, and spatial and temporal modeling (Bayesian and frequentist) Expertise in R or Python, GIS, big