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Field
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simulation - Scientific software development in C/C++, Fortran, and Python. - HPC/GPU computing - GIS, remote sensing, and geospatial analysis - Machine learning and deep learning Department Information
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for research teams. Apply analytical tools such as GIS, remote sensing, and statistical or computational methods to interpret field and greenhouse data. Prepare figures, summaries, and technical documentation
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collaboration with national and international stakeholders, the project aims to establish a validated, data-driven design framework. Key outcomes will include an open-source Python toolkit, measurable
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experience with large administrative or healthcare datasets Experience working with gridded environmental or climate datasets and spatial data analysis tools (e.g., R, Python, GIS) Strong technical writing
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, supporting precision agriculture applications, and assisting with geospatial data analysis (GIS and/or remote sensing). Laboratory and computational duties will involve data systems administration, processing
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Required Qualifications PhD in Animal Science, Environmental Science, Agronomy, Plant Science, Soil Science, Agricultural Engineering, or related quantitative field. Demonstrated experience in GIS-based
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Qualifications) • Experience with externally funded research (e.g., NSF, USDOT, NIH, or similar). • Experience contributing to grant or proposal development. • Familiarity with transportation data, GIS
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, tracking, spatio-temporal modeling, edge learning) using field data (traffic cameras, micromobility telemetry, connected vehicle/V2X, crash records, GIS). · Manage and coordinate pilot deployments
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, or Python Creativity in problem solving Demonstrated ability to absorb a broad array of information from a diversity of fields Strong written, oral, and interpersonal communication and presentation skills
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Our main research themes are: Life and its Interactions with Dynamic Environments, and Global Landscapes & Climate Change. PhD: 3-4 years full-time; 6-8 years part-time; Thesis of Max 80,000 words MSc (Research): 1-2 years full-time; 2-3 years part-time; MPhil: 2-3 years full-time; 3-4 years...