Postdoctoral Researcher - Metabolomics

The Institute of Molecular Systems Biology (IMSB) at ETH Zurich invites applications for a Postdoctoral Researcher in Metabolomics & Technology Development in the laboratory of Prof. Dr. Nicola Zamboni
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Prof. Dr. Nicola Zamboni’s team studies how metabolism functions and is regulated. The group focuses on systems in which metabolism or metabolites influence phenotypic differentiation and biomedical processes, particularly in complex or technically challenging settings. To address these questions, the lab develops and applies new methods for metabolomics, lipidomics, and ¹³C metabolic flux analysis, as well as for data processing, integration, and interpretation.

Current research directions include, for example, applying DIA-based strategies in large-scale studies, combining electron- and photon-activation methods for structural analysis of metabolites and lipids, creating metabolomics knowledge graphs, and inferring fluxes from MS data. The group collaborates with mass spectrometry vendors and technology partners to evaluate emerging instrumentation and software and translate them into robust, scalable workflows.

Alongside method development, the Zamboni Lab is tightly embedded in numerous collaborations with academic, clinical, and pre‑clinical groups, for which it provides measurements as well as expertise in the interpretation and integration of metabolomics data. The lab is a pillar of the Swiss Multi‑Omics Center (SMOC) and contributes state‑of‑the‑art metabolomics and lipidomics capabilities to large consortia, including activities connected to personalized health.

The lab is seeking a postdoctoral fellow who will integrate with the existing team and support both in the development of new concepts and in delivering high‑quality measurements to partners and collaborators. The exact focus will be tailored to the candidate’s strengths and evolving opportunities in the field.

• Contribute to LC–MS/MS method development and benchmarking, with a strong focus on untargeted workflows (DIA/DDA) and scalable, robust acquisition strategies.
• Design, execute, and document high‑quality measurements for internal projects and external collaborations, including appropriate QC, troubleshooting, and clear reporting of results.
• Operate and optimize automated sample preparation workflows, including liquid‑handling robotics (method set‑up, optimization, validation, and QC).
• Drive untargeted data processing workflows (feature extraction, alignment, QC metrics, drift/batch correction) and reporting.
• Advance annotation strategies using modern approaches such as spectral/structure fingerprinting, molecular networking, in‑silico annotation, and emerging machine‑learning and generative methods for spectra or structure proposals.
• Evaluate and test emerging technologies (hardware and software) in close interaction with collaborators and vendors, translating promising ideas into reliable pipelines.
• Contribute to instrument performance monitoring and maintenance, including routine upkeep and first‑line troubleshooting in coordination with the team.
• Collaborate effectively with team members, clinical/pre‑clinical partners, and consortium stakeholders (e.g., SMOC‑related activities), aligning deliverables and timelines.
• Support training and knowledge transfer (tutorials, onboarding, best‑practice documentation).
• Represent the lab at conferences and scientific meetings through talks, posters, and networking.
• Contribute to scientific manuscripts and publications.

• A genuine passion for metabolomics and technology development with an impact mindset (turning ideas into usable capabilities).
• PhD in analytical chemistry, bioengineering, biochemistry, computational biology, systems biology, or a related field.
• Strong hands‑on expertise in high‑resolution LC–MS/MS, with proven experience in metabolomics, lipidomics, or exposomics.
• Demonstrated experience with untargeted acquisition and study workflows (DDA/DIA), including QC concepts and reproducible practices.
• Deep knowledge of untargeted processing pipelines (feature extraction, alignment, adduct/isotope handling, QC metrics, drift/batch…