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for Learning Analytics at the University of Pennsylvania—each of which is advancing cutting-edge work at the intersection of AI and education. The NTO also maintains active partnerships with leading educational
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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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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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Mellon University, the SCALE Initiative at Stanford, and the Penn Center for Learning Analytics at the University of Pennsylvania—each of which is advancing cutting-edge work at the intersection of AI and
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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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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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researchers. · Strong analytical, organizational, communication, and problem-solving skills, attention to detail, and ability to handle multiple tasks simultaneously. Preferred Qualifications · Experience with
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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