Estonian National Graduate Trainee in AI/Machine Learning Mapping of Forestry Biodiversity
EsaFrascati · Posted Sep 15
Location: Frascati, IT
Estonian National Graduate Trainee in AI/Machine Learning Mapping of Forestry Biodiversity
Job Requisition ID:
20892
Date Posted:
15 September 2026
Closing Date:
13 October 2026 23:59 CET/CEST
Publication:
External Only
Type of Appointment (learn more):
ESA Graduate Trainee
Directorate:
Earth Observation Programmes
Workplace:
Frascati, IT
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Grade Band (learn more):
F1 - F1
The ESA National Graduate Trainee (NGT) Programmes offer recent Master’s graduates the opportunity to gain practical, hands-on experience at ESA across a range of space-related disciplines. The programmes are essentially similar to ESA’s own Graduate Trainee Programme, notably in offering the same employment conditions. They however differ in one important respect: each NGT Programme is funded by an individual ESA Member State or Associate Member under a bilateral partnership agreement concluded with ESA. As a result, a representative of the sponsoring State participates in the selection process. In addition to assessing candidates against the requirements of the position, the selection may also include an evaluation of their background and knowledge of the space policies and related activities of the sponsoring State.
Location
ESRIN, Frascati, Italy
Our team and mission
The Applications Section primarily engages in research and development (R&D) focused on Earth observation-based solutions that contribute to addressing the European and global international environment and development agenda. Our projects typically involve active collaboration with Early Adopters at every stage, including design, development, and validation. This ensures the seamless integration of innovative EO-based solutions into end-user operational systems and practices. The team is based at the ESRIN site of ESA and comprises nine Earth observation (EO) experts. Each expert specialises in overseeing specific domains where EO data are applied. The Applications team is part of the Green Solutions Division (eo4society - eo science for society).
You are encouraged to visit the ESA website: http://www.esa.int
Field(s) of activity/research for the traineeship
About 21% of the world’s forest area is currently designated under legal protection. These forests are highly valuable for carbon storage and sustaining biodiversity. However, high annual rates of tree cover loss continue to this day, with impacts both on forest carbon stocks and their biodiversity. It therefore remains difficult to assess how effective protected area designation is as a forest conservation tool. The legal status of a protected area does not automatically mean that active protection is being implemented, particularly in regions with limited financial resources for conservation.
ESA’s Sentinel missions are widely used to monitor forests by providing frequent, consistent, and freely available satellite data on forests. In April 2025, ESA also launched the BIOMASS mission with a novel P-band synthetic aperture radar designed to deliver crucial information about forest conditions, changes, and their role in the carbon cycle. As an NGT, you will utilise BIOMASS mission data in synergy with several other EO missions (particularly the Sentinels) to achieve the following:
Develop forest (a) carbon and (b) structural/functional biodiversity indicators for protected areas.
Map land cover and land cover change within protected boundaries using long-term EO time series, comparing trends inside protected areas with surrounding unprotected lands.
Evaluate ecosystem condition, for example by tracking vegetation health, fragmentation, or recovery after disturbance.
Summarise key findings that will concisely and accurately inform international/national policies aimed at forest conservation.
You will utilise ESA-supported cloud computing platforms for conducting your research. By the end of the traineeship, you will have gained practical experience in scalable Earth observation processing, applied analytical methods for land monitoring, product validation and uncertainty assessment, and stakeholder-driven development in an international setting. You will also develop a broader understanding of how EO-derived forest information supports international policy and reporting frameworks.
Technical competencies
Knowledge of relevant technical/functional domains
Relevant experience gained during internships, project work and/or extracurricular or other activities
General knowledge of the space sector and relevant activities
Knowledge of ESA and its programmes/projects
Behavioural competencies
Result Orientation
Operational Efficiency
Fostering Cooperation
Relationship Management
Continuous Improvement
Forward Thinking
For more information, please refer to ESA Core Behavioural Competencies guidebook
Education
You should have just completed, or be in the final year of your master’ s degree in Forestry, Remote Sensing, Data Science, Environmental Science, or a related engineering discipline.
Additional requirements
You should have good interpersonal and communication skills and should be able to work in a multicultural environment, both independently and as part of a team. Previous experience of working in international teams can be considered an asset. Your motivation, overall professional perspective and career goals will also be explored during the later stages of the selection process.
In addition to the standard requirements, the following would be considered an asset:
Experience with Earth observation for land cover mapping and multi temporal satellite data processing; familiarity with forest ecosystems is an asset.
Strong programming skills (e.g. R, Python), including geospatial data processing.
Knowledge of machine learning and deep learning for image and time series analysis; experience with cloud or high performance computing environments is an asset.
Ability to communica
Details
- Work type
- Onsite
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