Estonian National Graduate Trainee in AI/Machine Learning Mapping of Forestry Biodiversity

ph3Estonian National Graduate Trainee in AI/Machine Learning Mapping of Forestry Biodiversity /h3 pJob Requisition ID: 20892 /p pDate Posted: 15 September 2026 /p pClosing Date: 13 October :59 CET/CEST /p pPublication: External Only /p pType of Appointment (learn more): National Graduate Trainee /p pDirectorate: Earth Observation Programmes /p pWorkplace: Frascati, IT /p pGrade Band (learn more): F1
- F1 /p h3Location /h3 pESRIN, Frascati, Italy /p h3Our team and mission /h3 pThe Applications Section primarily engages in research and development (RD) 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). /p h3Field(s) of activity/research for the traineeship /h3 pAbout 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. /p pESA’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: /p ul liDevelop forest (a) carbon and (b) structural/functional biodiversity indicators for protected areas. /li liMap land cover and land cover change within protected boundaries using long-term EO time series, comparing trends inside protected areas with surrounding unprotected lands. /li liEvaluate ecosystem condition, for example by tracking vegetation health, fragmentation, or recovery after disturbance. /li liSummarise key findings that will concisely and accurately inform international/national policies aimed at forest conservation. /li /ul pYou 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. /p h3Technical competencies /h3 ul liKnowledge of relevant technical/functional domains /li liRelevant experience gained during internships, project work and/or extracurricular or other activities /li liGeneral knowledge of the space sector and relevant activities /li liKnowledge of ESA and its programmes/projects /li /ul h3Behavioural competencies /h3 ul liResult Orientation /li liOperational Efficiency /li liFostering Cooperation /li liRelationship Management /li liContinuous Improvement /li liForward Thinking /li /ul pFor more information, please refer to ESA Core Behavioural Competencies guidebook /p h3Education /h3 pYou 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. /p h3Additional Requirements /h3 pYou 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. /p pIn addition to the standard requirements, the following would be considered an asset: /p ul liExperience with Earth observation for land cover mapping and multi temporal satellite data processing; familiarity with forest ecosystems is an asset. /li liStrong programming skills (e.g. R, Python), including geospat