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some of the following areas (not all are required): Large-scale data analysis and learning analytics methods Experimental or quasi-experimental design; validity and measurement Working with LLMs
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on study design, validation workflows, and result interpretation, with an emphasis on building local analytical capacity and ensuring reproducibility. Approximately 3-4 weeks of international travel will be
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studies. Lifespan developmental perspectives linking psychological factors to health. Cutting-edge quantitative analytic methods. Core responsibilities include: Conducting data analysis for ongoing projects
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funding. Anticipated Division of Time Research & Tool-building (60%) – Geospatial/RS analytics; model design and validation; reproducible workflows. Stakeholder Collaboration (20%) – Co-develop decision
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%) - Geospatial/RS analytics; model design and validation; reproducible workflows. Stakeholder Collaboration (20%) - Co-develop decision tools; synthesize partner data; occasional site visits across NYS
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existing national datasets (including remotely sensed data) and will conduct a mixed-methods data collection campaign that emphasizes mapping intervention-specific adoption, adoption outcomes and identifying
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molecular biology techniques such as DNA extraction, PCR, or qPCR. Experience analyzing biological data using command line tools, R, SAS, or similar analytical software. Familiarity with bioinformatic
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(e.g., transcriptomics, proteomics, metabolomics) - Microscopy methods, FT-IR spectroscopy, or other analytical imaging techniques - Analysis of next-generation sequencing data - Programming skills (e.g
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, contribute to data visualization, figure preparation, and professional scientific writing. (30%); Assist in the development of proposals for external funding for research projects. (5%) Requirements Required
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, or field settings. Experience with molecular biology techniques such as DNA extraction, PCR, or qPCR. Experience analyzing biological data using command line tools, R, SAS, or similar analytical software