Experienced Postdoctoral Researcher in Computational Functional Genomics | Experienced Postdoc Researcher in Development and application of computational methods for functional genomics

ETH Zürich

Basel, BS, Switzerland
Published Nov 19, 2025
Full-time
Permanent

Job Summary

Join the Laboratory for Biological Engineering at ETH Zurich in Basel to develop and apply innovative computational methods for cutting-edge functional genomics datasets. This role is crucial for advancing genome engineering technologies, focusing on in vivo single-cell CRISPR perturbation screens (Perturb-seq) and transcriptional recording (Record-seq). The Postdoc Associate will be responsible for building, maintaining, and documenting scalable, reproducible analysis pipelines using Python/R and workflow managers like Snakemake/Nextflow. You will develop and apply sophisticated statistical methods and machine learning models (PyTorch/JAX on HPC) for demultiplexing, cell-type annotation, and perturbation prediction, as well as integrating complex multi-omics data (metagenomics, transcriptomics). The ideal candidate holds a PhD in Bioinformatics or a related field and possesses substantial postdoctoral experience in handling large-scale biological datasets. This is a highly collaborative position within an international, interdisciplinary environment, requiring mastery of English, offering the chance to co-author high-impact biological and technological publications.

Required Skills

Education

PhD or equivalent in Bioinformatics, Computational Biology, Computer Science, Applied Statistics, or a related field.

Experience

  • Substantial postdoctoral or equivalent experience developing and applying computational methods to large-scale biological datasets.
  • Extensive prior experience in strong Python and R skills, solid software engineering practices, and a track record of building scalable, reproducible pipelines for large-scale in vivo perturbation and multi-omics datasets.
  • Demonstrated experience analyzing deep sequencing and single-cell data, including large-scale in vivo Perturb-seq or related CRISPR-based perturbation screens.
  • Extensive prior experience developing pipelines and analytic workflows for novel molecular technologies (such as transcriptional recording).

Languages

English (Fluent)

Additional

  • Ability to communicate effectively in a highly interdisciplinary and international environment. Must be able to use and maintain lab resources on High-Performance Computing (HPC) and Github.