In der aktuellen Covid-19 Situation laufen die Rekrutierungen weiter. Es kann dabei allerdings zu Verzögerungen kommen. Vielen Dank für Ihr Verständnis.

Post-Doctoral Researcher - Computational Metabolomics

80%-100%, Zurich, fixed-term

The Institute of Molecular Systems Biology at ETH Zurich is inviting applications for a Postdoctoral position in the laboratory of Professor Dr Nicola Zamboni.

Project background

The group of Dr Zamboni researches the function and regulation of metabolism. In particular, the group is attracted by

  • systems in which metabolism or metabolites drive phenotypic differentiation
  • problems of biomedical relevance, and
  • cases that are especially complex or technically challenging

To tackle such problems, the group adopts cutting-edge mass spectrometry (i.e. metabolomics, lipidomics, and quantitative 13C metabolic flux analysis) and computational methods. The latter range from statistics to deep learning or probabilistic graphical models, and aim at integrating prior knowledge on molecular properties or network topology.

A key focus of the group is on the development of high-throughput methods, which allow to rapidly screen large cohorts of, i.e. clinical samples, drug libraries, or mutant collections. By combining high-resolution, untargeted mass spectrometry and newly engineered software pipelines, the group has become very efficient in analyzing studies with tens of thousands of samples without compromising quality and coverage. Beyond internal R&D projects, the group of Dr Zamboni is heavily involved in external collaborations, both national and international. The group is tightly embedded in the Swiss initiatives on personalized health (PHRT, Here, the main focus is on complementing metabolomics and lipidomics data with tools that assist in data integration and interpretation.

Job description

  • Expand our infrastructure for feature annotation by MS2 spectra (library-based, de novo structural generation, molecular networks, etc.).    
  • Interact with mass spectrometrist and MS vendors to improve data acquisition (DIA, DDA, real-time spectral analysis, etc) and processing workflows. 
  • Coordinate data integration efforts with our partners in the PHRT initiative 
  • Assist, advise, and train lab colleagues and students on analysis of metabolomics data.

Your profile

  • A doctoral degree in computer science, machine learning, computational chemistry or a related field.
  • Sound experience with deep and self-supervised learning, probabilistic graphical models
  • Solid understanding of the techniques and computational challenges that are state-of-the-art in computational metabolomics.
  • A genuine passion for metabolomics
  • A proactive personality and excellent communication skills.

ETH Zurich

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.
Working, teaching and research at ETH Zurich Link icon


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

  • CV
  • A motivation letter stating own visions and specifying any past experience that is aligned with the job profile
  • Name and contact of two referees

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

Further information about the Institute of Molecular Systems Biology can be found on our website, Questions regarding the position should be directed to Dr Nicola Zamboni, email (no applications).

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Your workplace