Full Professional Researcher – Krummel lab

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

Position Description

Full Professional Researcher – Krummel lab The Krummel lab in the Department of Pathology seeks a computational scientist to help lead the UCSF Custom Immunoprofiler project (co-led by the Krummel and Combes labs at UCSF), applying single-cell genomics and machine learning to patient tumor samples and to in vivo and ex vivo perturbation models in murine and human tumors to identify, prioritize, and validate therapeutic targets. The work builds on our immune archetype framework of discrete tumor microenvironment states hypothesized to represent distinct tumor ecosystems that predict therapeutic response.

Key Responsibilities

• Lead the computational strategy and analysis for the Custom Immunoprofiler projects, applying single-cell genomics and machine learning to patient tumor samples to identify and prioritize therapeutic targets.
• Oversee and perform end-to-end scRNA-seq analysis, from raw data (FASTQ) through standardized pipelines into analysis-ready objects in Seurat (R) or Scanpy (Python), with rigorous quality control, normalization, and integration.
• Apply and extend consensus non-negative matrix factorization (cNMF) and related approaches to define gene expression programs and characterize their variation across patients and experimental conditions.
• Interpret results in biologically and clinically meaningful ways, and assemble analysis packages and reports suitable for review by the group and external stakeholders and collaborators.
• Propose and develop new analytical initiatives and methods, including machine learning approaches for therapeutic target identification and prediction of treatment response.
• Partner closely with experimental and clinical investigators to design and interpret in vivo and in vitro perturbation experiments that validate computational predictions.
• Work with project leads to co-mentor and train junior bioinformaticians, and establish best practices for reproducible workflows, documentation, and scalable computational pipelines.

Required Qualifications

• Ph.D. (or equivalent degree) in bioinformatics, computational biology, computational immunology, genomics, or a related field, with two or more years of post-degree experience, by the time of hire.
• Demonstrated ability to independently lead computational analyses and interpret results in close collaboration with experimental and clinical teams.
• Strong proficiency in R and/or Python.
• Deep, demonstrated experience analyzing single-cell RNA-seq data with Seurat and/or Scanpy.
• Experience developing or applying machine learning methods to genomic or biological data.
• Experience with high-performance computing environments and reproducible workflows.
• Applicants' materials must list current and/or pending qualifications upon submission.

Preferred Qualifications

• Hybrid expertise spanning experimental and computational approaches (preferred, not required).
• Track record of close collaboration with experimentalists (highly preferred).
• Experience mentoring and training junior staff.
• Experience with single-cell spatial transcriptomics.
• Familiarity with tumor immunology, the tumor microenvironment, and/or patient class discovery.

See Table 13B for the salary range for this position. A reasonable estimate for this position is $141,200 - $257,100.

Document Requirements

• Curriculum Vitae - CV must clearly list current and/or pending qualifications (e.g. board eligibility/certification, medical licensure, etc.).
• Cover Letter (Optional)
• Statement of Research (Optional)
• Statement of Teaching (Optional)

Reference Requirements

• 2 required (contact information only)

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.

UCSF is committed to welcoming and serving all people, honoring the dignity of every individual without preference or prejudice, in support of its public mission and in alignment with our PRIDE values and Principles of Community.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

Disclosure

• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, or discrimination, as defined by the employer.
• UC Sexual Violence and Sexual Harassment Policy
• UC Anti-Discrimination Policy
• APM - 035: Aff...

San Francisco, CA