Postdoctoral Researcher – Ontologies and Semantics

Somma; País Vasco; Presencial; EUR 40.000 - 70.000; Jornada completa

Descripción de la vacante

Una empresa innovadora busca un Especialista en Semántica y Ontología para unirse a un equipo diverso y contribuir al desarrollo de una infraestructura web semántica. Este puesto implica la creación de recursos semánticos y la integración de datos para abordar problemas ambientales y de sostenibilidad. Con un enfoque en el modelado de sistemas humanos-naturales, el candidato ideal tendrá un doctorado y experiencia en proyectos de I+D. Ofrecemos un entorno de trabajo interdisciplinario y la oportunidad de participar en actividades académicas, todo en un espacio inspirador y tranquilo. Si deseas hacer una diferencia en el ámbito de la sostenibilidad, esta es tu oportunidad.

Servicios

Ambiente de trabajo interdisciplinario

Espacios de trabajo tranquilos y amplios

Participación en actividades académicas

Formación

• Se requiere un doctorado en áreas relacionadas con la web semántica.
• Experiencia previa en proyectos de I+D y modelado de ecosistemas.

Responsabilidades

• Contribuir al desarrollo de semánticas robustas para sistemas socio-ecológicos.
• Desarrollar herramientas para facilitar la anotación semántica.

Conocimientos

Programación en Java

Integración de datos

Modelado de ecosistemas

Experiencia en proyectos de I+D

Análisis de datos geoespaciales

Conocimiento de vocabularios comunitarios

Trabajo en equipo

Comunicación en inglés

Educación

Doctorado en Ciencias de la Computación

Máster en campos relacionados

Herramientas

SPARQL

RDF / OWL

ARIES

Descripción del empleo

The Basque Centre for Climate Change (BC3) offers a full-time postdoctoral scientific-technical position to work as a Semantic and Ontology Specialist to support the research activities of Research Line (RL) 5 on Integrated Modelling of Coupled Human-Natural Systems, under the unit of excellence Maria de Maeztu´s scientific plan.

About the project :

The project aims to develop a globally applicable, open-source semantic knowledge base for the ARIES project, building on and supporting 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 decision-making and research aimed at sustainable development.

Contribute to the ARIES platform, a semantic web infrastructure that uses AI to build computational solutions to environmental, policy and sustainability problems. This technology, based on machine reasoning, machine learning, distributed / high-performance computing and multi-disciplinary and multi-paradigm system modelling, is serving a growing number of worldwide users (from academia, governments, NGOs and industry). ARIES’ current semantic resources have addressed the challenge of using ontologies capable of supporting machine reasoning to address interdisciplinary science problems, reusing existing semantic authorities whenever possible and creating novel semantic content when needed. This position will continue to grow ARIES’ semantic resources to address further novel modeling challenges.

As the definition of living and social systems is multi-domain, touching on the semantically diverse dimensions of vegetation, soil, biodiversity, agriculture, and the economic and social systems, the problem of characterizing ecosystems semantically is very complex and hardly suitable for a traditional, dichotomic ontology approach. The candidate will contribute to the improvement and continued development of the ARIES “worldview”, a set of ontologies capturing semantics from several scientific domains and community-endorsed vocabularies. The worldview is the basis for all the ARIES functionalities and enables automated, adaptive and flexible model-building through machine reasoning.

The specialist will work with a team of programmers and modelers on diverse scientific modeling and integration applications to:

• Research existing authoritative semantic resources and integrate them with ARIES where possible.
• Create new semantic resources as needed.
• Co-develop tools to make semantic annotation easier and more intuitive for scientists with limited exposure to semantics.
• Develop and build community within and beyond the ARIES team around the application of semantics to environmental modeling.

Key responsibilities :

• Contribute to the building of robust, flexible, and interoperable semantics for socio-ecological system characterization and analysis over time.
• Contribute to model development and data integration within the ARIES platform, working closely with a 25+-strong team representing diverse cultural and disciplinary backgrounds.
• Broadly contribute to the ARIES platform, a semantic web infrastructure that uses AI to build computational solutions to environmental, policy and sustainability problems.

Main skills required :

• Hold a PhD degree for developing the tasks of the job description (a master’s degree at minimum), e.g. a degree in Computer Science, ICT, Computational Linguistics, Geomatics, Ecoinformatics, Geography, Ecology, Biology, and fields related to the Semantic Web.
• Previous experience in R&D projects (min of 2 years).
• Experience with Linked Open Data and query technologies on knowledge graphs (e.g. SPARQL, RDF / OWL), ontology authoring.
• A background in one or more of: ecology and sustainability, geography, economics, sociology, 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 harmonising data from diverse sources.
• Understanding of geospatial data formats and standards.
• Proficiency in programming languages, particularly the Java platform.
• Ability to develop scripts and tools for data processing and integration.
• Experience in teamwork and ability to interact with a broad range of scientific collaborators.
• Flexibility to work on diverse tasks and integrate new tools and methodologies as needed.
• Experience with distributed version control and project management.
• Ability to work independently within a diverse, multi-location and multi-lingual team.
• Excellent written and oral command of English (Spanish is a plus, as well as other languages).

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.