Computational Scientist II

Computational Scientist
About the Role
We are seeking a highly motivated and collaborative Computational Scientist to join the Li Lab / Geiger-Schuller Lab / Regev Lab within Research and Early Development (gRED). The successful candidate will derive actionable insights from high-content perturbation screens of ex vivo systems. This role requires a deep understanding of computational methods for analyzing sequencing-based, multi-conditional perturbation data (e.G. Sci-plex, Perturb-seq, CROP-Seq), a passion for innovation, and a commitment to improving healthcare outcomes through cutting-edge technology.
Key Responsibilities
Analyze large-scale high-content sequencing-based perturbation datasets
Collaborate with interdisciplinary and cross-functional teams including biologists, chemists, data scientists, and other stakeholders.
Qualifications
Educational Background: PhD degree in quantitative field (e.G., Computational Biology, Bioinformatics, Computer Science, Statistics, Mathematics) or in the physical or life sciences (e.G., Chemistry, Biology) with a strong quantitative focus.
Experience:
Proven track record of analyzing large-scale multi-conditional scRNA-seq datasets
Demonstrated interest in problems across biology and chemistry as applied to the discovery and development of treatments for disease.
Technical Skills:
Proficiency in scientific programming in Python.
Strong background in statistics, probabilistic modeling and data analysis.
Soft Skills: Excellent communication, collaboration, and problem-solving skills.
Publications: Strong publication record and experience contributing to research communities.
Preferred
Experience with the analysis of Perturb-seq/CROP-seq data, or more generally with CRISPR data
Multimodal data integration, in particular between multiple measurement modalities and/or clinical patient data
Experience with workflow managers such as nextflow or snakemake
Practical experience with working on HPC systems / SLURM