Postdoctoral Position in Computational Genomics, Machine Learning & Single-Cell Biology

Postdoctoral Position in Computational Genomics, Machine Learning & Single-Cell Biology
EPFL - Swiss Federal Institute of Technology Lausanne
Geneva, Switzerland
Mission
The Zenk Lab (NeuroNA Chair in Epigenomics of Neurodevelopmental disorders – EpiGN) is seeking a highly motivated postdoctoral researcher with strong training in computational biology and/or machine learning to join an interdisciplinary project at the interface of single-cell genomics, data integration, and developmental biology.
The project focuses on the integration and analysis of multi-modal single-cell datasets, including scRNA-seq, scATAC-seq, scCUT&Tag, HiC, and proteomics, with an emphasis on trajectory inference, regulatory dynamics, and cell fate decisions. A key goal is to integrate multimodal data using machine learning approaches to uncover principles of cellular state transitions. The work will be carried out in close collaboration with other labs at EPFL, offering a uniquely rich environment combining experimental biology and computational genomics.
Main duties and responsibilities
Working and collaborating on research projects
Analysis and publication of results
Build a strong network in the field of research
Participate in education, and PhD and master student supervision
Profile
Strong background in computational biology, bioinformatics, machine learning, or a related quantitative field
Experience with machine learning and/or statistical modeling applied to biological data
Proven expertise in single-cell data analysis (scRNA-seq and/or scATAC-seq)
Interest or experience in multi-modal data integration and trajectory inference
Proficiency in Python and/or R
Interest in developmental and human biology is highly valued, but not required
Strong collaborative mindset and ability to work across disciplines
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EPFL - Swiss Federal Institute of Technology Lausanne