Postdoctoral Position in Computational Genomics, Machine Learning & Single-Cell Biology — EPFL
CHF 60'500 - 91'500
EPFL · Genève (GE)
- Location
- Genève
- Contract
- full-time
- Posted
- 48 days ago
SalaryCHF 60'500 - 91'500
Role overview
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 , 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.
- 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 , HiC, and proteomics, with an emphasis on trajectory inference, regulatory dynamics, and cell fate decisions.
- Main duties and responsibilities
- Working and collaborating on research projects Analysis and publication of results
Main responsibilities
- 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 We offer
Additional details
- Working and collaborating on research projects Analysis and publication of results
- Interest or experience in multi-modal data integration and trajectory inference Proficiency in Python and/or R
Notes and original content
- Working and collaborating on research projects
- Analysis and publication of results
- Interest or experience in multi-modal data integration and trajectory inference
- Proficiency in Python and/or R
