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the framework of the project using statistical methods. - Contribution to academic publications based on project’s results. - Administrative support of the project, its events and activities. The employment
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of sample processing and method development with multiple contract research organizations relating to toxicity, ADA and sample storage/labelling/stability studies will also be key responsibilities
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reconciliation, enhancement, and integration of the MLGB dataset, working with legacy print, manuscript, and digital sources. You will apply and adapt digital methods (especially TEI XML), analyse provenance data
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to learn unfamiliar tools as needed (e.g. GitHub, APIs, new libraries). Familiarity with econometric techniques, especially panel data methods. Clear, concise written and verbal communication skills. Ability
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, environmental data science, or a closely related STEM discipline Demonstrated expertise in urban spatial data analytics, with proficiency in GIS software (e.g. QGIS, ArcGIS) and geospatial methods Experience in
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, highly motivated researchers that both enjoy working in a team but capable of working independently. They should be keen to utilize eclectic theories and methods, develop new theoretical perspectives while
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 6 hours ago
for the position of research assistant professor with a significant outreach component. Expectations of the position will be to develop an externally supported research program in agroforestry and contribute
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collaborative team engaged in a range of research projects in marine hydrodynamics, both computational and experimental. This is a fully on-site role, with work taking place in the office and laboratory. We
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or worsening structural and clinical features and identify risk factors for decline among severely affected children with CZS. Dr. Kelleher’s research uses telehealth-based methods to assess early development
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🚀 Graduate Student Positions Available!The HECS lab (new lab starting in Fall 2025) in the Department of Electrical Engineering and Computer Science (EECS) at University of Arkansas is currently