About the position
Work duties Forests differ substantially in their species composition, structure and ecological function, with tree-species diversity influencing biodiversity, ecosystem services, resilience to environmental disturbance, and contributing to nature-based solutions. The project assistant will primarily involve preparing and integrating large geospatial datasets, adapting and applying machine-learning models across different forest and environmental conditions, and evaluating model performance using forest inventory and other reference data. The position will also involve producing national-scale tree-species and species-composition maps, assessing spatial patterns of prediction uncertainty, and carrying out quality control of the resulting map products. Additional tasks may include processing satellite and ancillary environmental data, preparing training and validation datasets, manual interpretation and digitization of reference information. Qualifications Master’s degree in environmental science, GIS, remote sensing, or equivalent competence. Experience analyzing large volumes of medium-resolution satellite remote sensing data such as Landsat and Sentinel-2. Very good programming skills (e.g. Python, JavaScript). Very good oral and written proficiency in English. Other merits Experience with time series satellite image analysis in cloud computing platforms (e.g. GEE Python API). Experience developing machine learning models (e.g. CNN, XGBoost, etc). We will place great emphasis on personal suitability. In the assessment, consideration will also be given to factors such as attention to detail, the ability to plan and organize work effectively, good collaboration skills, initiative, and independence. Consideration will also be given to how the applicant’s experience and competencies complement and strengthen the research activities within the project. Terms of employment Fixed-term employment, 8 months. The scope of the employment, full time (100%). Instructions on how to apply Applications should be in English and include a cover letter stating the reasons why you are interested in the position and in what way the employment corresponds to your qualifications. The application should also contain a CV, degree certificate or equivalent, and other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.). Welcome to apply!
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