Important Info
Please submit Required Application Materials to Gernot Kaber (gkaber@stanford.edu).
The Betof Warner Lab at Stanford University School of Medicine is seeking a highly motivated postdoctoral fellow to join our team focused on advancing the understanding and efficacy of tumor-infiltrating lymphocyte (TIL) therapies for melanoma. This position offers a unique opportunity to work at the intersection of cutting-edge cancer immunotherapy and advanced computational biology.
Position Overview:
• Full-time postdoctoral position in computational biology/bioinformatics
• Focus on analyzing multi-omic data from melanoma patients receiving TIL therapies
• Co-mentorship by Dr. Allison Betof Warner and Dr. Zinaida Good
Key Responsibilities:
• Adapt internal computational pipelines to analyze high-dimensional patient datasets, including single-cell sequencing, spatial transcriptomics, clinical, and other relevant correlative data.
• Integrate and interpret diverse data types to gain insights into TIL therapy outcomes and mechanisms
• Collaborate with wet-lab researchers and clinicians to translate findings into actionable hypotheses
• Present findings at lab meetings, conferences, and in peer-reviewed publications
• Contribute to grant writing and project planning
• Ph.D. in Computational Biology, Bioinformatics, Computer Science, or a related field
• Strong programming skills in R and/or Python
• Experience with analysis of single-cell sequencing data
• Familiarity with spatial transcriptomics analysis
• Interest in cancer biology and immunology principles
• Excellent written and verbal communication skills
Preferred Qualifications:
• Experience with machine learning approaches for biological data analysis
• Knowledge of tumor microenvironment and cancer immunotherapy concepts
• Track record of peer-reviewed publications in relevant fields
• Experience with cloud computing, version control systems (e.g., Git), and reproducible research practices
• Ph.D. in Computational Biology, Bioinformatics, Computer Science, or a related field
• Strong programming skills in R and/or Python
• Experience with analysis of single-cell sequencing data
• Familiarity with spatial transcriptomics analysis
• Interest in cancer biology and immunology principles
• Excellent written and verbal communication skills
• Cover letter detailing your research experience and interest in this position
• CV including publication list