Data and Knowledge Engineering

Data and Knowledge Engineering

The Swiss Data Science Center (SDSC) is a joint venture between EPFL and ETH Zurich. Its mission is to accelerate the adoption of data science and machine learning techniques within academic disciplines of the ETH Domain, the Swiss academic community at large, and the industrial sector. In particular, it addresses the gap between those who create data, those who develop data analytics and systems, and those who could potentially extract value from it. The centre is composed of a multi-disciplinary team of data and computer scientists and experts in selected domains, with offices in Zürich, Lausanne, and Villingen.

• Characterize, harmonize and standardize the SDSC projects’ metadata;
• Collaborate with domain experts to implement processes, standards, and Semantic Web Technologies;
• Provide specifications and develop programming interfaces for semantic integration of heterogeneous research data; 
• Design and implement semantic graph technologies for organizing data, semantic data annotation, ontology representation and visualization, SPARQL endpoints; 
• Promote internal and external data sharing, curate and prepare FAIR (findable, accessible, interoperable, and re-usable) datasets;
• Provide consultation and support for the SDSC research projects;
• Write documentation, develop and provide tutorials and training.

We are looking for an engineer passionate about open and reproducible research to join the SDSC (Lausanne or Zürich office). As the data and knowledge engineer, you will join SDSC projects to secure knowledge representation and ensure data transparency, accessibility, and interoperability. Furthermore, you will bring your experience in semantic graph technologies and ontology development to bring innovative ideas into working prototypes. In addition, you will closely collaborate with the SDSC Renku platform team to further knowledge discovery through the Renku knowledge graph.

• A stimulating, collaborative, cross-disciplinary environment in a world-class research institution;
• Flexible work arrangements, including remote working, flexible time, condensed week, and the opportunity to work part-time;
• Exciting challenges, varied projects, and plenty of room to learn and grow;
• An opportunity to follow your passion and use your skills to make an impact on research communities and society;
• A possibility to spark your creativity by experimenting and learning new technologies;

You are an engineer with an MSc or higher degree in Computer Science or related fields. You are fascinated by Knowledge Representation and Semantic Technologies and enjoy discovering how people think. Likewise, you have experience with ontologies, knowledge engineering, and data curation and modeling, preferably in the medical, environmental, or public administration domains. Your career journey has taken you through projects involving graph databases, triple stores, and graph query languages. You are passionate about graph visualization methods and readily share your achievements with diverse audiences (ideally in English plus German or French). You aspire to use semantic text mining and natural language processing (NLP) to support knowledge extraction - we will celebrate if you already have such experience.

ETH Zurich is one of the world’s leading universities specialising in
science and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.

We look forward to receiving your application with the following documents:

• Motivation letter
• CV
• Diplomas

Please note that we only accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information can be found on our website www.datascience.ch . If you have questions regarding the position please email [email protected] (no applications).

For recruitment services the GTC of ETH Zurich apply.