Postdoctoral Researcher in Ecological Modeling


The Basque Centre for Climate Change (BC3) offers a full-time postdoctoral scientist position in order to support the research activities of Research Line (RL) 5 on Integrated Modelling of Coupled Human-Natural Systems, and specifically work on the international project OBServ.

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 in order to support an effective policy-making where nature counts. Besides Ecosystem Services, the RL also tackles Natural Capital Accounting, Food Security, Marine Spatial Planning, and Renewable Energy.


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 and with multiple model integration types to predict complex change. It also supports selection of the most appropriate data and models using cloud technology and following an open data paradigm: the resulting insight remains open and available to society at large, and becomes a base for further computations, contributing to an ever-increasing knowledge base. For the first time, it is possible to consistently characterize and publish data and models for their integration in predictive models, building and field-testing technologies that have eluded researchers to date.

The OBServ project focuses on building predictive models of pollinator biodiversity and ecosystem function delivery using both data-driven and mechanistic models.

We are looking for an individual who can support strategic activities related to integrated data science and collaborative, integrated modelling on the semantic web (semantic meta-modelling).

Job description: Contribute to the ARIES (ARtificial Intelligence for Environment and Sustainability) platform, a semantic web infrastructure that uses artificial intelligence (AI) to build computational solutions to environmental, policy and sustainability problems. This technology, based on machine reasoning, machine learning, distributed computing and high-performance, multi-disciplinary and multi-paradigm system modelling, is the flagship product of the Integrated Modelling Partnership (IMP) which is expected to serve a growing number of worldwide users (from academia, governments, NGOs and industry) in the years to come.

ARIES’ current model resources largely focus on ecosystem services, using diverse modeling paradigms including machine learning and deductive models. The modeler will work as part of a team to develop and test new models that expand the breadth of ARIES’ model library, including ecosystem services and other environmental models at scales from local to global. Data-driven models built with a variety of machine learning classifiers have been applied so far to land cover change modelling, biodiversity modelling (, water quality modelling and pollination modelling. The candidate will work to expand the use of ML libraries (e.g., Weka) and applications beyond the state of the art.

The position may require international travel on an as-needed basis.

Key responsibilities:

  1. Collaborate in building, evaluating and delivering integrated models within the ARIES platform. The OBServ project focuses on pollination as a central piece for the modelling and simulation of agri-systems and biodiversity, but the position will entail multi-disciplinary applications;
  2. Collaborate in building, evaluating and delivering complexity-oriented models of coupled human-environmental systems;
  3. Integrate such models and their results within a holistic, integrated trade-off assessment framework for decision- and policy-making;

Main requirements:

  1. The applicant must have a degree in computer science, ecology, geography, engineering, or other fields of relevance to ecoinformatics. A very strong background in computational modelling is required, along with programming skills (any language and in particular Python, Java, R and Julia).
  2. Familiarity with any of the following methods is an asset: agent-based modelling, network analysis, Bayesian network modelling, system dynamics. Being initiated to ontologies, artificial intelligence, and machine reasoning is desirable. Familiarity with any of the following technologies is an asset: Git, GeoServer, Linux, RESTful web services, openCPU, JSON.
  3. The applicant must have excellent interpersonal and communication skills. Excellent written and oral command of English is required. An ability to work in teams and experience in the use of collaborative software platforms and distributed version control systems are necessary.
  4. Applications including previous modelling works and their documentation in an online repository will be given priority.

Term of contract

The position will be for a period of 6 months


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 a HR Excellence awarded institution, BC3 is committed to conciliate research-academic requirements and family duties. BC3 is particularly concerned with creating equality opportunities for people. Women with relevant qualifications are therefore strongly encouraged to apply for the position.

Application procedure:

Those interested should include in their request:

  1. 2-pages CV
  2. one-page motivation letter
  3. Two referees


25th May 2021 (CET 17:00).

Informal enquiries can be made to Ferdinando Villa ( and Stefano Balbi ( noting in the subject of the message “ARIES ML scientist”

  • The personal information you provide through this job offer, will be registered in the data processing systems responsibility of BC3 for the purpose of managing your participation in the current selection process. This personal information will not be communicated to any recipient except those required by law, and will not be used for any other purpose different than the one stated here.
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Proyecto PCI2018-093175 financiado por MICIN/AEI/10.13039/501100011033 y cofinanciado por la Unión Europea

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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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