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Field
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conceptual modeling, and experience in semantic modeling, ontology engineering, formal logics or cognitive modelling; affinity with maps, geospatial concepts, GIS systems, and spatial data infrastructures
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), recognition on Stanford University's World’s Top 2% Scientists list (2022–present), the IADR William J. Gies Award (2023), election as a Fellow of the American Institute for Medical and Biological Engineering
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
learning. Interest in tropical ecology, public health, and sustainable development. Experienced and highly skilled in GIS and remote sensing. Strong communication skills and an interest in stakeholder
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Postdoctoral Research Associate in Financial Accounting Gies College of Business Postdoctoral Research Associate Department of Accountancy We seek a full-time postdoctoral research associate to work
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), recognition on Stanford University's World’s Top 2% Scientists list (2022–present), the IADR William J. Gies Award (2023), election as a Fellow of the American Institute for Medical and Biological Engineering
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currently at Duke working with Duke GI T32 mentors are expected to submit a detailed research proposal (limit 3 pages). Other Duke applicants and any external applicants should instead submit a 1-2 page
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We are seeking a Postdoctoral Researcher in Geospatial Urban Big Data to support the analysis of urban dynamics and decision-making in territorial planning. The candidate must be proficient in GIS
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of statistical analyses and modelling. Experience in handling and analyzing large datasets. Experience in employing high performance and cloud computing services. Knowledge in GIS. Knowledge on obtaining
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of statistical analyses and modelling. Experience in handling and analyzing large datasets. Experience in employing high performance and cloud computing services. Knowledge in GIS. Knowledge on obtaining
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procedures used in spatial data analysis and vegetation dynamics modeling is required. The candidate should have extensive practical experience in the use of R and GIS. Demonstrated skills of Bayesian modeling