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

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

The Zenk Lab (Neuro

NA 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.

• 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

• 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

• A highly interdisciplinary research environment at the interface of ML and biology
• Access to large, state-of-the-art single-cell multi-omics datasets
• Close collaboration with leading groups in single-cell genomics and machine learning
• Strong support for high-impact publications and career development