Technical Scientific Modelling – MARBEFES Project

The Basque Centre for Climate Change (BC3), offers a full-time technical scientific modelling position on the MARBEFES (MARine Biodiversity and Ecosystem Functioning leading to Ecosystem Services) Horizon project – HORIZON-CL6-2021-BIODIV-01-03 – dedicated to marine biodiversity and ecosystem functioning  to ensure that they deliver ecosystem services, goods and benefits and using the ARIES (ARtificial Intelligence for Environment & Sustainability) platform.

A key focus of ARIES is to integrate spatially explicit ecological and economic models to examine the link between ES and impacts on the socioeconomic status but also on environmental outcomes. Furthermore, to analyze potential future consequences of alternative land uses for both nature conservation and economic objectives. By developing spatially explicit models and incorporating in the analysis landscape scenarios it is possible to study the effect of changing features on ES dynamics. Analyzing the spatial dynamics of ES can provide a complete understanding of the supply and flows of particular benefits for specific beneficiary groups and enable to evaluate better trade-offs in environmental management.

The ARIES platform supports all activities of BC3 Research Line (RL) 5 on Integrated Modelling of Coupled Human-Natural Systems. The (, is a semantic web infrastructure that uses AI to build computational solutions to environmental, policy and sustainability problems. The RL generates multidisciplinary scientific knowledge from human-nature interdependence to address complex sustainability problems through artificial intelligence (AI).

The goal of the RL is to provide environmental data, models and understanding by retrieving, evaluating, and integrating the existing information to support an effective policy-making where nature counts. Besides Ecosystem Services and Biodiversity, the RL also tackles Natural Capital Accounting, Conservation Finance, Food Security, Marine Spatial Planning, and Renewable Energy. All these products are used to inform sustainability decisions, e.g. SDGs.

Job description:

We are looking for a technical scientific modelling skills who can support research projects and the development of ARIES technical tasks.

The researcher will be participating in various activities throughout the project, such as:

  • Internal coordination of the data resources used by the ARIES teamwork within BC3.
  • Technical support in the development of the ARIES platform and in relation to ongoing research projects that use it, especially the MARBEFES project ( and its modelling, scenario, upscaling and out scaling development and application components (WP 5-6).
  • Technical support in the development of the Marine Biodiversity and Valuation Toolbox to be delivered under MARBEFES project.
  • Coordinating with external project partners and stakeholders.

 Key responsibilities:

  • Support model development and data integration within ARIES platform.
  • Support the data management and coordination within ARIES platform, especially, but not only, for the MARBEFES project.
  • Technical support in relation to ongoing ARIES research activities, and particularly those related to MARBEFES.
  • International travelling and participation to meetings when required.
  • Presentation of main achievements at international conferences.
  • Collaborate in the semantic and ontological developments of ARIES.

Main requirements/skills:

  • Suitable degree for developing the tasks above (a master’s degree at minimum).
  • Previous experience in R&D projects (min of 8 years)
  • Excellent written and oral command of English
  • Previous exposure to Open Source Software related projects.
  • Experience in geospatial data processing, management and modelling.
  • A working knowledge of geomatics and in particular open source GIS and standards/protocols to expose geospatial assets.
  • Experience in programming (any language and in particular Python and Java).
  • Ability to participate in teamwork and interact with a broad range of collaborators.
  • Ability to work independently, with a diverse, multi-location and multi-lingual team.
  • Experience in agile management and in particular issue and project tracking.

 Desirable requirements:

  • Familiarity with ecosystem services and/or environmental modelling.
  • Exposure to Git and collaborative software development technologies.
  • Experience in project coordination and management.
  • Excellent interpersonal and communication skills.

 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 on the September 2024, the position will be granted until the end of the MARBEFES project (November 2026), with a six-month probation period.




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


30th June 2024 (CET 15:00).

Informal enquiries can be made to Marta Pascual ( noting in the subject of the message Technical Scientific modeler”.

Please consider that only applications sent through the form included at the bottom of the BC3 web page will be considered (

MARBEFES — HORIZON-CL6-2021-BIODIV-01 is funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

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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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