The NCCR Catalysis (Sustainable Chemical Processes Through Catalyst Design, has the ambition to make the production of commodity chemicals and fuels sustainable and carbon neutral, and therefore to contribute to mitigate climate change. ETHZ will be leading house and EPFL co-leading house, with many other Swiss educational centers participating. The mission of the data officer will be to develop a scalable research data management system based on data standardization, storing, sharing, and processing in the field of catalysis research. You will be part of the NCCR management team office located at ETHZ, whereas yourself will be at EPFL. The candidate should have at least three years of experience in software-related positions with validated experience in large software architectures, data management and digitalisation.You will be located within the Institute of Chemical Sciences and Engineering (ISIC, at EPFL, and will have a privileged interaction as well with the Swiss Data Science Center (SDSC, Motivated and qualified candidates should submit their application online before 01.09.2020.


See the job ad for application requirements.


You will work on solving challenges with our industry partners. You will be involved in all aspects of a data science research project, from business understanding to proof of concepts and communication of achievements. You will design and test machine learning systems to solve industry challenges. Presenting data science results to a non-technical audience will also be part of your activities. During your work, you will have the opportunity to be coached by data scientists with an academic background as well as industry experts. When dealing with data engineering aspects, you will have the opportunity to collaborate with our system specialists. The academic environment will allow you to grow your machine learning and statistics skills thanks to trainings.


We are looking for creative engineers to join our ranks. As a member of our team, you will be asked to develop, deploy and monitor the various services of our data science platform. Our engineering and operations team loosely follows an agile methodology and we expect all of our members to contribute their unique viewpoints to the overall decision making. The platform we are building is extremely multi-faceted which means that our team is equally varied and eager to learn. As a critical part of the development and deployment process, we actively collaborate with data scientists from the academia and industry to gather requirements for improving the usability of our platform.
LOCATION: Lausanne and Zurich