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consisting of Cornell and agency scientist. Specifically, the individual will: 1) Analyze acoustic data with existing software (Echoview, R, Python). 2) Collaborate with USGS scientists on field data
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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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within an interactive research group consisting of Cornell and agency scientist. Specifically, the individual will: 1) Analyze acoustic data with existing software (Echoview, R, Python). 2) Collaborate
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to drive informed, effective decisions is required. The ideal candidate will be fluent in using statistical coding languages such as Python, R and SQL to query large datasets from a data warehouse and create
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and innovation engagement. Strong familiarity with STEM fields, university recruiting, and corporate R&D interests. Ability to operate with agility across organizational boundaries and strategic
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transforming academic citations in multiple formats such as APA. Experience and skill using different software packages and web-based tools (e.g., statistical software (e.g., R, Stata, or SAS), Microsoft Office
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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
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and/or R (geospatial stacks, data wrangling, visualization). Record of peer-reviewed publications commensurate with career stage and strong scientific writing skills. Ability to work collaboratively
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/water/agricultural applications. Strong programming skills in Python and/or R (geospatial stacks, data wrangling, visualization). Record of peer-reviewed publications commensurate with career stage and
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and/or R (geospatial stacks, data wrangling, visualization). Record of peer-reviewed publications commensurate with career stage and strong scientific writing skills. Ability to work collaboratively