Modelling Ecosystem Types with Semantics

The Basque Centre for Climate Change (BC3) offers a full-time technical scientific modelling position on the World Ecosystem Extend Dynamics (WEED) project funded by the European Space Agency from 2024 to 2026. The project aims to develop a globally applicable, open-source knowledge base and toolkit for a comprehensive mapping of the extent and distribution of ecosystem types, according to different ecosystem typologies, and for monitoring the temporal variations in ecosystem extent. The project builds on the research activities of Research Line (RL) 5 of BC3 on Integrated Modelling of Coupled Human-Natural Systems.

During the past decade, the RL has envisioned and built the ARIES (ARtificial Intelligence for Environment and Sustainability ( platform, a technology that integrates network-available data and model components through semantics and machine reasoning. Its underlying open-source software (k.LAB, handles the full end-to-end process of integrating data with multiple modelling paradigms. A key focus of ARIES is to integrate spatially and temporally explicit ecological and economic models to support Natural Capital Accounting, which includes ecosystem extent and services.

Job description:

As the definition of ecosystem types is multi-domain, touching on the semantically different dimensions of vegetation, soil, biodiversity, agriculture and more, the problem of characterizing ecosystems semantically is very complex and hardly suitable for a traditional, dichotomic ontology approach. The candidate will contribute to the development of an ecosystem extent ARIES authority that will merge semantics from community-endorsed vocabularies from all corresponding dimensions, connecting to the reasoning engine in ARIES by turning flexible ecosystem specifications into reasoning-ready concepts. The authority will support the definition of different ecosystem typologies and will enable any possible crosswalk between them, while also assessing and documenting uncertainty in cases where crosswalk results remain ambiguous.

More broadly,  the researcher will work with a team of programmers and modelers on diverse scientific modeling and integration applications to (1) research existing authoritative semantic resources and integrate them with ARIES where possible, (2) create new semantic resources as needed, (3) co-develop tools to make semantic annotation easier and more intuitive for scientists with limited exposure to semantics, and (4) develop and build community within and beyond the ARIES team around the application of semantics to environmental modeling.

Key responsibilities:

  • Contribute to the research project dedicated to mapping ecosystem types using semantics and develop robust, flexible, and interoperable models for ecosystem characterization and analysis over time.
  • Contribute to model development and data integration within the ARIES platform, working closely with a 20+-strong team representing diverse cultural and disciplinary backgrounds.
  • Coordination of project tasks and meetings with the WEED project collaborators.
  • National and international travelling and participation in project meetings when required.
  • Broadly contribute to the ARIES platform, a semantic web infrastructure that uses AI to build computational solutions to environmental, policy and sustainability problems.

Ideal requirements and skills:

  • Suitable degree for developing the tasks of the job description (a master’s degree at minimum), e.g. a degree in Computer Science, ICT, Geomatics, Ecoinformatics, Geography, Ecology, Biology.
  • Previous experience in R&D projects (min of 2 years).
  • Exposure to semantic web technologies such as Resource Description Framework (RDF and SPARQL), Web Ontology Language (OWL) and knowledge representation techniques.
  • Solid background in ecosystem science, including vegetation, soil, biodiversity, and agriculture.
  • Familiarity with community-endorsed vocabularies and standards in domains such as vegetation, soil, biodiversity, and agriculture.
  • Understanding of ecosystem typologies (e.g. IUCN Global Ecosystem Typology, EUNIS) and land system classifications (e.g. the FAO Land Cover Classification System).
  • Experience in ecosystem modelling (experience with ARIES is a plus).
  • Proficiency in integrating and harmonizing data from diverse sources.
  • Understanding of geospatial data formats and standards.
  • Proficiency in programming languages such as Java, Python, or R.
  • Ability to develop scripts and tools for data processing and integration.
  • Excellent written and oral command of English (Spanish is a plus, as well as other languages).
  • Experience in teamwork and ability to interact with a broad range of scientific collaborators.
  • Experience with distributed version control, issue tracking and project management.
  • Ability to work independently, within a diverse, multi-location and multi-lingual team.
  • Flexibility to work on diverse tasks and integrate new tools and methodologies as needed.

Benefits and work environment:

  • Interdisciplinary and inspiring work environment
  • Quiet and spacious workspaces
  • Possibility of participating in internal training and academic activities of the center
  • 35-hour week work calendar
  • 30 days of vacation per year

Term of contract

Starting in September 2024, the position will be granted until the end of 2026, with a six-month probation period. Opportunities for continuation beyond the project’s end will be available depending on performance, funding and fit with the team.



The position will carry competitive salary, matching the academic and professional profile of the applicant, and excellent work conditions.


Basque Centre for Climate Change, Leioa, Spain.

As an HR Excellence awarded institution, BC3 is committed to conciliating research-academic requirements and family duties. BC3 is particularly concerned with creating equal opportunities for people independently of gender, culture, and race. Anyone with relevant qualifications is therefore strongly encouraged to apply for the position.

Application procedure:

Fill the form below and upload one PDF document with the following information:

  1. Curriculum Vitae (2 pages)
  2. Letter of motivation of a page
  3. Contact details of two referees


15th August 2024 (CET 15:00).

Informal enquiries can be made to Stefano Balbi ( noting in the subject of the message “MODELLING ECOSYSTEM TYPES WITH SEMANTICS

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María de Maeztu Excellence Unit 2023-2027 Ref. CEX2021-001201-M, funded by MCIN/AEI /10.13039/501100011033

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