CSO
The Computational Systems Oncology lab integrates algorithmic design, data science, and molecular biology approaches to address relevant questions in cancer biology and therapeutics.

Our group is embedded within the Department of Computational Biology of the University of Lausanne and a member of the Swiss Cancer Center Leman, the Swiss Institute of Bioinformatics, and Institute for Experimental Cancer Research (ISREC) @EPFL

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Cancer Evolutionary Dependencies

Cancer emerges through the occurrence and selection of molecular alterations. We aim at understanding factors that favor or veto selection of specific alterations, a.k.a. evolutionary dependencies (EDs). In particular, we focus on concurrent or mutually exclusive selection of genetic alteations and whether these EDs can inform response to therapy.

Cancer Cell Plasticity

Cancer cells can change their phenotype or even their identity without modifying their genetic code. We are interested in understanding epigenetic and transcriptional reprogramming programs that underlie cancer cell plasticity. We study features of plastic reprogramming among different patients and within individual tumors, using cutting edge single cell and spatial -omics technologies.

Chromatin 3D Architecture

A key paradigm in biology is that structure determines function. Whether and to what extent this holds true for chromatin 3D architectures remains an open question. Here, we study chromatin structural changes in response to cancer genetic variants and epigenetic reprogramming. Our goal is to decipher chromatin plasticity and determine how it is hijacked in and/or it influences tumor phenotypes.

Currently open positions:

  • Ph.D. student and Post-doc positions available in our lab!

    (UPDATED JULY, 2025) We are looking for outstanding candidates for Ph.D. student and post-doctoral positions in our group!
    We're opening multiple positions to study cancer evolution through the lens of spatial transcriptomics and multi-modal single-cell analyses. The successful applicant will work in interdisciplinary team combining development and application of new algorithmic approaches, high-throughput data generation, and functional genomics approaches.

    Requirements
    For the post-doctoral positions, a Ph.D. in computer science or related field and at least one first/main author publication in a peer-reviewed journal are required. Previous experience in cancer genomics and single-cell omics is preferred.

    To Apply
    Just send me an email with your CV and name of 3 referees.
    if you can't figure out my email..maybe you shouldn't apply
    Cheers!