Lead Computational Immunoprofiling Scientist

University of California, San Francisco; San Francisco (CA); On-site; USD 141,000 - 257,000; Full time

Job summary

University of California, San Francisco seeks a Full Professional Researcher to lead the UCSF Custom Immunoprofiler project in the Krummel lab. The role combines single-cell genomics and machine learning to analyze patient tumors and perturbation models to identify therapeutic targets.

You will supervise end-to-end scRNA-seq workflows, use Seurat or Scanpy, and collaborate with experimental and clinical teams to translate analyses into actionable insights and publications.

Qualifications

• PhD in bioinformatics, computational biology, or related field with two+ years post-degree experience.
• Ability to independently lead computational analyses in collaboration with experimental teams.
• Strong proficiency in R and/or Python.
• Deep experience analyzing single-cell RNA-seq data with Seurat/Scanpy.
• Experience applying machine learning to genomic/biological data.
• Experience with HPC environments and reproducible workflows.

Responsibilities

• Lead the computational strategy and analysis for Custom Immunoprofiler projects.
• Oversee end-to-end scRNA-seq analysis from raw data to analysis-ready objects.
• Apply cNMF and related methods to define gene programs across patients.
• Interpret results and assemble analysis reports for review by collaborators.
• Develop new analytical initiatives including ML approaches for targets.
• Collaborate with experimental/clinical teams to design in vivo/in vitro studies.
• Co-mentor junior bioinformaticians and promote reproducible pipelines.

Skills

Lead computational analyses

R

Python

Single-cell RNA-seq analysis

Seurat

Scanpy

Machine learning

HPC/reproducible workflows

Education

PhD in bioinformatics or related field

Tools

Seurat

Scanpy

R

Python

High-performance computing

Job description

University of California, San Francisco seeks a Full Professional Researcher to lead the UCSF Custom Immunoprofiler project in the Krummel lab. The role combines single-cell genomics and machine learning to analyze patient tumors and perturbation models to identify therapeutic targets.

You will supervise end-to-end scRNA-seq workflows, use Seurat or Scanpy, and collaborate with experimental and clinical teams to translate analyses into actionable insights and publications.