Job description: During the past decade, the RL has envisioned and built the 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 data and model integration 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 develop a way to consistently characterize and publish data and models for their integration in predictive models, building and field-testing languages and technologies that have eluded researchers to date.
Experience/skills required: 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).
The selected candidate will:
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.
In particular this is a postdoctoral research position dedicated to the use of semantics for solving complex sustainability problems. We are looking for an individual who can coordinate the work to establish the most comprehensive knowledge base to implement a Semantic Web for Sustainability.
The goal of the Semantic Web is to make Internet data machine-readable. To enable the encoding of semantics with the data, technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL) are used. These technologies are used to formally represent metadata. For example, ontology can describe concepts, relationships between entities, and categories of things. These embedded semantics offer significant advantages such as reasoning over data and operating with heterogeneous data source
The selected candidate should have:
- A PhD in Computer Science, ICT, Computational Linguistics, Philosophy of Information or any field related to the Semantic Web
- Strong analytical skills and an ability to learn quickly and to think outside the box. Our work is very innovative and you should expect your job to be both as intellectually challenging and as rewarding. A strong motivation and a desire to learn and explore new technologies are a must.
- A strong background in the development of Ontologies for scientific applications.
- Experience with RDF, OWL, Ontology editors (e.g., Protégée).
- Exposure to Upper Ontologies (e.g. DOLCE, BFO. SUMO), Observation Ontologies and Domain Ontologies (e.g. ENVO)
- Programming ability in any language, particularly Java, is considered an asset
- Excellent interpersonal and communication skills.
- Excellent written and oral command of English.
- Ability to work independently, with a diverse, multi-location and multi-lingual team.
