Job Description

Mission


We are 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 develop and apply machine learning approaches, ranging from probabilistic models to modern representation learning, to uncover principles of cellular state transitions. The work will be carried out in close collaboration with the Deplancke lab and the Brbić lab at EPFL, offering a uniquely rich environment combining experimental biology, computational genomics, and ML methodology.

Main duties and responsibilities

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