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minimum of one year eligibility remaining. Strong skills in technical programming languages, e.g., Matlab, Python, or C++; in computational statistics, i.e., unsupervised and supervised ML methods, incl
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of the appointment. Demonstrated proficiency in data analysis, statistical modeling, and data visualization using R, Python, or comparable analytical software. Evidence of effective scientific communication through
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: Statistical programming and data analysis using R, Python, or Matlab, Spatial data analysis or GIS Whole-genome sequencing, phylogenetics, or phylodynamics Data management and reproducible analytical workflows
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Science Minimum Requirements Background managing and analyzing large datasets, developing geospatial models and tools, familiarity with ESRI products or similar GIS software(s), proficient in programming in
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of hydrologic processes, transboundary/shared water resources management, and coupled human–natural systems. Proficiency in geospatial and scientific computing tools (e.g., Python, R, GIS, Google Earth Engine
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measurements. Proficiency in programming languages and data analysis tools such as Python, Matlab, and R. Proficiency in GIS software (e.g., ESRI ArcPro). Hydraulics of flood control and storm surge suppression
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analytical and quantitative skills, including statistical programming (e.g., R, Python, or similar). Knowledge of causal inference methods and/or comparative risk assessment approaches. Familiarity with
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
geospatial data processing and python programming. Candidates should also have knowledge of optical, lidar, and ground penetrating radar sensing systems and understanding of pavement structures and condition
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research for an NIH-NSF funded project on human health, movement, and infectious diseases. Successful applicants will have experience in: Either spatial analysis using GIS or disease modeling in R and/or
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, or modeling using tools such as Python, R, GIS, or similar computational platforms. Demonstrated ability to collaborate across disciplines and translate technical and social science insights into scholarly