During the past decade, the RL has envisioned and built the ARIES (ARtificial Intelligence for Environment and Sustainability (https://aries.integratedmodelling.org/) platform, a technology that integrates network-available data and model components through semantics and machine reasoning. Its underlying open-source software (k.LAB, https://docs.integratedmodelling.org/technote/) 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.
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 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 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 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.
This postdoctoral research position is dedicated to the use of semantics for solving complex sustainability problems. We are looking for an individual who can coordinate and support the work to establish the most comprehensive knowledge base to implement a Semantic Web for Sustainability. The researcher will work with a team of programmers, modelers and ontologists 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.
The goal of the Semantic Web is to make web-hosted data and models machine-readable. To enable the encoding of semantics that accurately and logically describe data and models, technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL) are used. For example, ontologies 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 sources.
- A PhD in Computer Science, ICT, Computational Linguistics, or fields 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 as intellectually challenging as rewarding. A strong motivation and a desire to learn and explore new technologies are a must.
- Experience with Linked Open Data and query technologies on knowledge graphs (e.g. SPARQL, RDF/OWL), ontology authoring,
- Working knowledge of description logics and first-order logic approaches.
- Exposure to formal ontologies, Semantic Web technologies, mainstream upper ontologies, conceptual modelling and knowledge integration for scientific applications.
- Programming ability in any language, particularly Java, is 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.