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Postdoctoral Fellow in Forest Remote Sensing and Climate Risk Assessment Lunds universitet in Sweden
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time, fixed-term postdoctoral employment for 2 years with possible extension. Teaching may be included up to 20% of working hours, with three weeks of higher-education teaching and learning training. No stipend amount is stated.
Deadline
Sep 27, 2026
Country
Sweden
University
Lund University
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About this position
Postdoctoral fellow position at Lunds universitet in Forest Remote Sensing and Climate Risk Assessment. The project develops an operational web-based service for Sweden’s forests using Landsat, Sentinel, tree-species maps, airborne lidar, canopy structure data, and climate indicators to produce drought-stress maps, storm-exposure hazard indices, and bark-beetle susceptibility signals.
The work combines forest ecology, environmental science, earth observation, geospatial data analysis, machine learning, and web GIS. The postdoc will build harmonized satellite time-series datasets, integrate ancillary data, develop automated update workflows and a user-facing dashboard, and study the spatial and temporal mechanisms linking windthrow, drought, and bark beetle outbreaks.
Eligibility requires a PhD or equivalent in physical geography, remote sensing, geoinformatics, forest ecology, environmental science, or a closely related field, completed within the last three years unless special circumstances apply. Strong Python skills, experience with Landsat/Sentinel time series, and a publication record are required. Experience with XGBoost, SHAP, HPC/cloud EO platforms, and lidar processing is especially valued.
This is a full-time, fixed-term 2-year appointment with possible extension. Teaching may account for up to 20% of working time, and the position includes three weeks of training in higher education teaching and learning. The application deadline is 2026-09-27.
Apply in English with a cover letter, CV including publications, doctoral degree certificate, other relevant certificates/grades, and contact details for two references via the university portal.
Funding details
Full-time, fixed-term postdoctoral employment for 2 years with possible extension. Teaching may be included up to 20% of working hours, with three weeks of higher-education teaching and learning training. No stipend amount is stated.
What's required
Applicants must have a PhD or equivalent in physical geography, remote sensing, geoinformatics, forest ecology, environmental science, or a closely related field, completed no more than three years before the employment decision unless special circumstances apply. Required experience includes satellite remote sensing for large-scale vegetation or forest monitoring, especially Landsat and/or Sentinel-1/2 time series, strong Python skills for geospatial analysis and machine learning (including XGBoost and SHAP), very good oral and written English, strong communication skills, ability to work independently and in a team, timely delivery of outputs, and a publication record in peer-reviewed international journals. Preferred merits include web-GIS development, geospatial visualization, HPC or cloud Earth observation platforms such as Google Earth Engine Python API, and airborne lidar/canopy height modelling.
How to apply
Prepare an English application with a cover letter (max 2 pages), CV with publications, doctoral degree certificate and other relevant certificates/grades, and contact details for two references. Submit via the university application portal before the deadline.
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