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/statistical skills Experience with statistical analysis software (e.g. R, SAS), GIS software (e.g., ArcGIS, QGis), and programming languages (e.g., R, Python, C++). Experience or interest in science integration
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periods. Excellent oral and written communication skills and be competent with Microsoft Office applications including Word, Excel, GIS. You will be willing to acquire or develop competence in XML. We
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free energy calculations using Free Energy Perturbation/Thermodynamic Integration (FEP/TI) to quantify binding affinity changes and receptor-Gi protein coupling alterations • investigate potential disulfide
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, Environmental Sciences, or Geography. Preferred conditions for the position include proven experience in Geographic Information Systems (GIS) and remote sensing tools (e.g., satellite data), as well as experience
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the CCDM, the Biometry and Agricultural Data Analytics team brings together biometricians, bioinformaticians, data scientists and GIS experts to solve problems for the Australian broadacre agriculture
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exposure to smart cities, IoT/sensor data, SCADA, GIS, or urban water management. EVALUATION CRITERIA The selection will be based on the following criteria: Academic merit and relevance (30%): grade history
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exposure to smart cities, IoT/sensor data, SCADA, GIS, or urban water management. EVALUATION CRITERIA The selection will be based on the following criteria: Academic merit and relevance (30%): grade history
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Postdoctoral Fellow in Anthropology: Meat, Infrastructure, and Zoonotic Risk on Chinas Belt and Road
around zoonotic risk. Map supply chains and infrastructural ecologies (in collaboration with project GIS support). Engage with veterinarians, traders, and health officials to trace multispecies and
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, Python, Julia, etc. Demonstrated experience working with spatial epidemiological, ecological, or environmental data, including hands-on use of GIS, spatial statistics, or other spatially relevant methods
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laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications relevant to environmental data analysis. Basic knowledge of GIS/mapping tools