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) • Big data pipelines, distributed computing, and geospatial data processing • Python, R, SQL/NoSQL, containerization (Docker), Kubernetes • API development and web-based analytics tools • Systems
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of the REST and XML protocols Professional experience in any modern object-oriented programming language (for example: C#, Java, PHP or Python.) Familiarity with Agile development methodologies **Sponsorship
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datasets. Proficiency in R and/or Python, with demonstrated experience developing reproducible analytical workflows (e.g., version control, well-documented code). Strongly Preferred Experience developing
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modeling in agricultural or environmental systems. • Proficiency in R, Python, or related analytical tools. • A record of peer-reviewed publications. Preferred Qualifications • Experience with livestock
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datasets. Proficiency in R and/or Python, with demonstrated experience developing reproducible analytical workflows (e.g., version control, well-documented code). Strongly Preferred Experience developing
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demand forecasting or behavior modeling Computing & Data Systems Cloud computing (AWS, Azure, GCP) Big data pipelines, distributed computing, and geospatial data processing Python, R, SQL/NoSQL
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spatial analysis. Experience with quantitative modeling in agricultural or environmental systems. Proficiency in R, Python, or related analytical tools. A record of peer-reviewed publications. Preferred
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, the individual will: 1) Analyze acoustic data with existing software (Echoview, R, Python). 2) Collaborate with USGS scientists on field data collections. 3) Investigate the spatial patterns of fish and
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on at least the following subjects: C and Python programming; digital logic and SoC on FPGA; and microcontroller systems; operating environments including embedded LINUX and other operating systems. Teaching
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in spatial analysis & GIS and remote sensing for land/water/agricultural applications. Strong programming skills in Python and/or R (geospatial stacks, data wrangling, visualization). Record of peer