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Field
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creation of a TxHC‑wide value–risk prioritization map to guide conservation investments. Design, administer, and analyze a landowner survey grounded in Protection Motivation Theory and participatory GIS
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may be approved only in exceptional circumstances or when required by the position's job duties. If you need assistance applying to this posting, please contact GI - Office of Human Resources at 907-474
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of the specific nature of these data (especially data from the AZP programme); advanced proficiency in GIS software; preferably experience in field archaeological research in loess areas, including
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new pollen analysis • Modeling and Statistics: Utilize GIS, R statistical environment, and other tools for pollen-based modeling (REVEALS and LOVE models) and statistical analysis. • Collaboration: Work
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questions related to infrastructure and development, and a thorough knowledge of applied econometrics The candidate should show some acquaintance in managing large datasets and non-traditional data, e.g. GIS
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structuring of river systems. Familiarity with software and tools for simulating river network dynamics, such as R, Julia, Python, or GIS-based hydrological modeling platforms. Ability to integrate physical
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for gastrointestinal (GI) cancers. Working within the O’Neill lab, you will play a central role in the collection, processing, maintenance, and characterisation of tumour and blood samples using a perfused culture
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, Natural Resources, Sustainability, or closely related field. Demonstrated expertise in spatial analysis & GIS and remote sensing for land/water/agricultural applications. Strong programming skills in Python
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such as surface hydrology, GIS-based spatial modeling, Artificial Intelligence (AI) and advanced data science. The successful candidate will engage in cross-disciplinary research with faculty from
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in spatial analysis & GIS and remote sensing for land/water/agricultural applications. Strong programming skills in Python and/or R (geospatial stacks, data wrangling, visualization). Record of peer