Post-Doctoral Researcher in Computational Metabolomics in Zürich

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

The group of Dr Zamboni researches the function and regulation of metabolism. It is particularly attracted by:

1. systems in which metabolism or metabolites drive phenotypic differentiation,
2. problems of biomedical relevance, and
3. cases that are especially complex or technically ambitious.

In its research, the group builds heavily on mass spectrometry for the analysis of the metabolome, the lipidome, and metabolic fluxes by stable isotopes. Beyond mere data generation, much of the current research activities are dedicated to formal integration and interpretation of omics data. These include a variety of computational methods ranging from statistics to deep learning and probabilistic graphical models.

The Zamboni lab hosts the Clinical Metabolomics Analysis Center, which is a technology hub affiliated with the Swiss initiatives on personalized health (PHRT, ). Thereby, it is tightly embedded in numerous projects and collaborations aiming at integrating deep molecular data into clinical decisions. Here, the focus of the Center is on democratizing metabolomics and lipidomics analyses for broad adoption in clinical research and diagnostic data streams. A speciality of the group is the development of high-throughput untargeted LC-MS methods. These are critical to swiftly screening large cohorts of clinical samples, drug libraries, or genetic mutants. With a steadily growing volume of samples and studies, novel opportunities emerge. These opportunities include learning across studies, implementing novel MS2 fragmentation strategies that maximize the amount of non-redundant information obtained in each study, aggregating different types of information for the task of structural elucidation, and exploiting novel types of fragmentation technology.

The Zamboni lab is seeking a postdoctoral fellow with strong computational skills and interests to strengthen developments in these forward-looking areas.

You are expected to:

• Expand our infrastructure for feature annotation by MS2 spectra (library-based, combinatorial approaches, de novo structural generation, molecular networks, etc.). The expansion can include both the creation of novel concepts and the engineering of existing methods for improved ease of use, scalability, and automatization.
• Lead independently and effectively own work and collaborative projects.
• Get along with MS experts and MS vendors to improve data acquisition (DIA, DDA, real-time spectral analysis, etc.) and processing workflows.
• Coordinate data integration efforts with our partners at PHRT.
• Assist and train colleagues and students on the analysis of metabolomics data.

Crucial qualifications:

• A doctoral degree in computer science, machine learning, bioinformatics, cheminformatics or a related field.
• Sound experience with deep and self-supervised learning, probabilistic graphical models
• Proven understanding of the techniques that are state-of-the-art in computational mass spectrometry and metabolomics.
• A passion for metabolomics and its role in enabling data-driven, personalized health.
• A proactive personality and excellent communication skills.

ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity and attractive offers and benefits.

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