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

h3Postdoctoral Position in Computational Genomics, Machine Learning Single-Cell Biology /h3pEPFL - Swiss Federal Institute of Technology Lausanne /ppGeneva, Switzerland /ph3Mission /h3pThe 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. /ppThe project focuses on the integration and analysis of multi-modal single-cell datasets, including scRNA-seq, scATAC-seq, scCUTTag, 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. /ph3Main duties and responsibilities /h3ulliWorking and collaborating on research projects /liliAnalysis and publication of results /liliBuild a strong network in the field of research /liliParticipate in education, and PhD and master student supervision /li /ulh3Profile /h3ulliStrong background in computational biology, bioinformatics, machine learning, or a related quantitative field /liliExperience with machine learning and/or statistical modeling applied to biological data /liliProven expertise in single-cell data analysis (scRNA-seq and/or scATAC-seq) /liliInterest or experience in multi-modal data integration and trajectory inference /liliProficiency in Python and/or R /liliInterest in developmental and human biology is highly valued, but not required /liliStrong collaborative mindset and ability to work across disciplines /li /ul #J-18808-Ljbffr