Postdoctoral Researcher - Computational Genomics, Machine Learning & Single-Cell Biology

About the role

The Zenk Lab (NeuroNA Chair in Epigenomics of Neurodevelopmental disorders – EpiGN) at EPFL is looking for a postdoctoral researcher with strong training in computational biology and/or machine learning. The project sits at the intersection of single-cell genomics, data integration and developmental biology, integrating multi-modal single-cell datasets (scRNA-seq, scATAC-seq, scCUT&Tag, HiC, proteomics) with a focus on trajectory inference, regulatory dynamics and cell fate decisions. The work is done in close collaboration with other EPFL labs.

Key responsibilities

• Work and collaborate on research projects
• Analyze and publish results
• Build a strong network in the research field
• Take part in teaching and supervise PhD and master students

Required profile

• Strong background in computational biology, bioinformatics, machine learning or a related quantitative field
• Experience applying machine learning and/or statistical modeling 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
• Interest in developmental and human biology is highly valued but not required
• Collaborative mindset and ability to work across disciplines

Required skills

• Proficiency in Python and/or R
• Single-cell data analysis (scRNA-seq, scATAC-seq)

What we offer

• A highly interdisciplinary research environment at the interface of machine learning 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

Contract starts on 06/01/2026, full-time, fixed-term contract of 12 months (reference 2072).