Department of Biosystems Science and Engineering
The Laboratory for Biological Engineering (Prof. Randall J Platt) at ETH Zurich in Basel, Switzerland, is at the forefront of developing genome engineering technologies. Our research spans various fundamental and disease-focused areas. To further enhance our initiatives, the Platt group is seeking a full-time (100%) experienced researcher to develop and apply computational methods for novel experimental functional genomics datasets.
Research Focus
Our lab establishes high-throughput experimental platforms that necessitate equally innovative computational methods. The successful candidate will contribute to two primary areas:
- In vivo Single-Cell CRISPR Perturbation Screens: We are revolutionizing the study of gene function at scale through CRISPR perturbation screens, including our recently developed AAV-based method for direct in vivo single-cell CRISPR screening. This project aims to generate comprehensive in vivo cell-type perturbation atlases and identify therapeutic targets, necessitating scalable pipelines for data analysis and machine learning approaches.
- Transcriptome Recording and Cellular History Reconstruction: We are advancing our CRISPR-based transcriptional recording method to capture transient cellular events. The selected candidate will tackle computational challenges in detecting biological signals in complex in vivo environments, while developing bespoke tools and workflows for analyzing novel data modalities.
Key Responsibilities
The candidate will engage in the following activities:
- Develop analytical methods and execute experimental designs, focusing on target gene selection and data analysis.
- Build and maintain scalable, robust, and reproducible analysis pipelines using tools such as Python/R, Snakemake/Nextflow, and Hydra.
- Create and apply statistical methodologies for data normalization, effect-size estimation, and predictive modeling, with an emphasis on biologically grounded models and machine learning techniques.
- Design strategies to integrate multi-omic datasets to uncover biological mechanisms in various contexts.
- Collaborate closely with experimental biologists to extract biological insights and contribute to publications.
- Use and maintain lab resources on HPC and GitHub.
Ideal Candidate Profile
The ideal candidate will possess:
- A PhD or equivalent degree in Bioinformatics, Computational Biology, Computer Science, Applied Statistics, or a related field.
- Significant postdoctoral experience developing computational methods for large-scale biological datasets.
- Excellent communication skills in a highly interdisciplinary and international environment, particularly in oral and written English.
Essential Experience
The candidate should have extensive prior experience in:
- Proficient skills in Python and R, solid software engineering practices, and a proven track record of building scalable analysis pipelines.
- Analyzing deep sequencing and single-cell data, especially in relation to large-scale in vivo CRISPR screens.
- Statistical methodology related to experimental design and perturbation-effect estimation.
- Designing bioinformatics workflows and utilizing HPC/cloud computing for machine learning applications.
- Developing pipelines for novel molecular technologies and applying methods to real biological datasets.
- Multi-omic data analysis and integration.
Additional Qualifications (Preferred)
Experience in the following areas is a major plus:
- CRISPR screen analysis and guide demultiplexing.
- Metagenomics, meta-transcriptomics, and metabolomics.
- Machine learning frameworks such as PyTorch and JAX.
- Genome-scale metabolic modeling.
Location and Environment
This position is based in the Department of Biosystems Science and Engineering (D-BSSE) at ETH Zurich in Basel, Switzerland. D-BSSE is a highly interdisciplinary department specializing in systems and synthetic biology, bioinformatics, and engineering sciences. Our location within a biomedical research hub fosters collaborations with prestigious academic institutions and biotechnology companies. Basel itself is a vibrant city offering easy access to arts, culture, and the beautiful landscapes of Europe.
Application Process
To apply, please utilize the application form below. Only applications matching the job profile will be considered.