Postdoc in Computational Systems Biology and Metabolic Modeling

Dysregulation of lipid metabolism plays a key role in the development and progression of metabolic disorders, including obesity, type 2 diabetes, and metabolic dysfunction-associated steatotic liver disease (MASLD). We are seeking a highly motivated Scientist in Computational and Systems Biology to work on a project funded by the Swiss National Science Foundation (SNSF) aimed at advancing our understanding of human lipid metabolism in MASLD. The project focuses on modelling human metabolism by integrating clinical data with experimental models. It involves biochemical and molecular data from multiple tissues and biofluids to investigate tissue-specific metabolism, metabolic interactions across organs, and nutrient uptake, transformation, and release. The project combines statistical modelling, systems biology, and in silico metabolic modelling with clinical, transcriptomic, proteomic, metabolomic/lipidomic, spatial molecular imaging, and experimental metabolic flux data to provide new insights into the complex metabolic alterations underlying MASLD.

What you can expect

<br />

• Develop and apply mathematical, statistical, and machine-learning models to complex, high-dimensional, and multimodal biological and clinical datasets, including spatial and imaging data
• Model lipid and nutrient metabolism using compartmental, kinetic, mechanistic, metabolic network, or physiologically based approaches
• Reconstruct and model tissue-specific metabolic networks and validate model predictions using experimental data
• Participate in and contribute to multidisciplinary and collaborative research projects.
• Prepare, present, and communicate scientific findings at internal meetings, international conferences, and through peer-reviewed publications

<br />

Your Profile

<br />

• PhD or equivalent in computational biology, systems biology, applied mathematics, biochemical engineering, or a related field
• Strong expertise in mathematical and statistical modelling, machine learning, and systems biology, with experience analysing high-dimensional, multimodal, or multi-omics biological or clinical data
• Demonstrated experience in in silico metabolic modelling, e.g. constraint-based or genome-scale metabolic modelling, metabolic network reconstruction, kinetic or metabolic flux modelling, or data-driven simulation
• Proficiency in R, Python, or MATLAB and experience integrating experimental data with computational models;
• Experience in mass spectrometry, spatial omics, molecular imaging, or tissue imaging is a strong asset
• Enthusiastic and collaborative scientist with strong analytical and problem-solving skills, the ability to work independently and in multidisciplinary teams, and excellent written and spoken English

<br />

What we offer

<br />

• A supportive, collaborative, and state-of-the-art research environment with opportunities for scientific and professional development
• Participation in multidisciplinary research projects at the interface of computational biology, systems biology, metabolism, multi-omics, molecular imaging, and clinical research
• The opportunity to work with large datasets from pre-clinical and clinical studies
• Close collaboration with experts from different scientific and clinical disciplines

<br />

Questions about the job?

For further information, please contact

Prof. Mojgan Masoodi
Head of Research

+41 31 66 4 05 32