Empa - the place where innovation starts
Empa is the research institute for materials science and technology of the ETH Domain and conducts cutting-edge research for the benefit of industry and the well-being of society.
The Urban Energy Systems Laboratory
carries out research into models and concepts for innovative building and decentralized energy system technologies. Our work is focused on achieving the energy transition where more of our energy is generated from clean, sustainable sources and energy efficiency is improved in every aspect. The planning of energy resources requires a clear and comprehensive understanding of the supply and demand and we believe that a digital transformation strategy is key to achieving this goal. To contribute to this challenge we are looking for a
Postdoc in the digital transformation of urban data for energy planning
You will contribute to projects that aim to improve the semantic interoperability of data used for planning in the energy sector. This will involve developing and applying data architectures to support energy planning at building, utility and municipal scale. The data will be supplied by living labs and demonstrators. The projects will involve close interaction and cooperation with project stakeholders and industry partners. The objective of this work is to provide a digital solution with demonstrable value to the energy planning industry. You will develop and apply data vocabularies that facilitate the development of decentralized applications. You will execute your research ideas in various projects, in close collaboration with our team and our external scientific and industry partners. You will support the dissemination of research findings across the knowledge community, which includes collaborating with other lab members and publishing in scientific journals and conferences.
We are seeking a highly motivated candidate with a PhD related to computer science, ideally with knowledge of linked data and semantic technologies. Ideally, you will have experience developing open-source applications and an interest in energy planning. Knowledge of upcoming data exchange initiatives such as GAIA-X would be advantageous. A scientific track record demonstrating the ability to work independently and as a team is essential.
Essential Skills: Python, experience of linked data technologies (RDF, SPARQL, and OWL), development and implementation of data models and data exchange.
Desirable Skills: Java, digital twins, policies for secure data exchange, cloud computing with platforms such as MS Azure, machine learning, languages (German, Italian), building information modelling (BIM), geospatial data analysis (GIS), energy planning concepts.