Post-Doctoral Researcher - Computational Metabolomics
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. 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, www.sfa-phrt.ch). Here, the main focus is on complementing metabolomics and lipidomics data with tools that assist in data integration and interpretation.
- 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.
- 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.
We look forward to receiving your online application with the following documents:
- 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, www.imsb.ethz.ch. Questions regarding the position should be directed to Dr Nicola Zamboni, email email@example.com (no applications).
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