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an understanding of large language models or conversational AI frameworks (e.g., OpenAI API, Gemini AI). You have experience setting up and maintaining databases (e.g. SQLite, MySQL). You have an
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. Experience with high-performance computing clusters or cloud-based Earth observation platforms (e.g., GEE Python API). Experience with airborne lidar data processing and canopy height modelling. We will place
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web-GIS development or geospatial data visualization. Experience with high-performance computing clusters or cloud-based Earth observation platforms (e.g., GEE Python API). Experience with airborne
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or automated data processing workflows Experience building APIs or data services for large scientific datasets Familiarity with the Model Context Protocol or similar systems for exposing data to AI tools and
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to review research by Francisco X. Aguilar, Professor (available here and on Google Scholar ), and coinvestigator Linus Andersson, Associate Professor, Docent (available here and on Google Scholar ). Please
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welcome applications until 30 September 2026 using the button below. Candidates are encouraged to review research by Francisco X. Aguilar, Professor (available here and on Google Scholar ), and
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An employment application must contain the following documents in English: A complete CV including short publication list, positions held, awards and prizes, link to Google Scholar profile. Whole CV no longer