Lund University, Faculty of Science, Centre for Environmental and Climate Science

Lund University was founded in 1666 and is repeatedly ranked among the world’s top universities. The University has around 47 000 students and more than 8 800 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Work duties
Forests provide several ecosystem services that are directly beneficial to human health and wellbeing. However not all forests are the same. Forests with a high diversity of tree species provide more ecosystem services and are more resistant to disturbances than forests with fewer tree species. The TreeSpec project is hosted at the Remote Sensing of Ecosystems research group at CEC and aims to map forest tree species across Sweden using satellite remote sensing and a data-driven approach.
The project assistant will be focused on the model development phase of the project. This involves using large volumes of forest inventory data for training different machine learning models to both classify tree species and map their proportions across the whole country. Other duties involve manual delineation of tree crowns of different species for use in semantic segmentation algorithms, creating interactive web maps of trees species, and digitizing maps.


  • Master’s degree in environmental science, GIS, remote sensing, or equivalent competence.
  • Minimum two years' experience developing machine learning models.
  • 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, R).
  • Excellent problem-solving skills.
  • Ability to work independently.
  • Very good oral and written proficiency in English.

Other merits

  • Experience with time series satellite image analysis in cloud computing platforms (e.g. Google Earth Engine).
  • Experience in semantic segmentation using convolutional neural networks (e.g. U-Net).
  • Experience developing interactive web mapping applications.
  • Good knowledge of European forest ecosystems and tree species.

We will place great emphasis on personal suitability. Consideration will also be given to, for example, attention to detail, time management skills, good collaborative skills, drive, and independence, and how the applicant’s experience and skills complement and strengthen the administrative work within the unit/department, as well as contribute to its future development.

Terms of employment

  • Fixed-term employment, 10 months.
  • The scope of the employment, full time (100%).
  • Contact person: Abdulhakim Abdi:

Instructions on how to apply
Applications should 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.).

Type of employment Special fixed-term employment
Contract type Full time
First day of employment As soon as possible or according to agreement
Salary Monthly
Number of positions 1
Full-time equivalent 100
City Lund
County Skåne län
Country Sweden
Reference number PA2024/1943
  • Hakim Abdi,
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-2229362
  • SACO:Saco-s-rådet vid Lunds universitet,
  • SEKO: Seko Civil, 046-2229366
Published 11.Jun.2024
Last application date 09.Jul.2024 11:59 PM CEST

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