Important Info
To apply, please submit the required application materials to The Kirane Lab at (kiranelab@stanford.edu)
The Department of Surgery Tumor Immunotherapy Lab, led by Dr. Amanda Kirane at Stanford University, is seeking a talented postdoctoral scientist to join the research team. Dramatic advances have been made in the treatment of melanoma and other checkpoint-responsive cancers, however, overall response is inadequate and significant adverse event rate remains high. Currently, there are no reliable predictive tools in clinical use and mechanisms of resistance to standard checkpoint therapy are poorly understood. Our lab joins the intersection of basic cancer immunology, patient-derived modeling, biomarker assay development, and novel spatial computational interrogation to take an immersive approach to this problem. The goal of this program is to perform high-quality research that utilizing clinical and basic mechanistic data to develop immediately usable, predictive tools for clinical testing.
Position Description
We are currently seeking a highly motivated Postdoctoral Trainee in the field of Cancer Immunology, Immunotherapeutics, and Computational Immunology. The successful candidate will work at the intersection of immunology, cancer biology, and bioinformatics with focus on the application of novel computational approaches, particularly spatial biology, to decode the complexities of immune response and therapeutic resistance in cancer. As a Postdoctoral Trainee, you will conduct groundbreaking and innovative research using techniques including, but not limited, to multiplex spatial IHC, genetic sequencing data analysis, study of immune cell signatures in tumor microenvironments, and immune response modeling. You’ll be encouraged to develop your independent research questions and methodologies under mentorship of expert staff and multidisciplinary collaborations in Materials Science, Engineering, Molecular Biology, and Bioinformatics.
Training overview:
- Individualized mentorship from a vibrant group of successful faculty from the Department of Surgery, the Stanford Cancer Center, Stanford Immunology, Stanford Engineering, and international collaborators in Bioinformatics and Bioassay design.
- Opportunities for didactic training in cancer research, immunology, clinical methodology, and bioinformatics.
- Access to a wealth of translational patient data from local and national leading studies as well as historic biospecimens.
- Clinical exposure through clinical trial design and clinic shadowing
- Opportunities to develop and apply for research grants and academic society sponsorship.
- Stanford University offers excellent benefits and competitive salaries.
Funding support is available for 1 year with renewal up to 3-5 years of training.
- Completed PhD or MD, or another relevant doctoral degree, including but limited to Immunology, Cancer Biology, Cancer Therapeutics, Computational and Data Sciences.
- An interest in studying melanoma and melanoma metastases. Previous experience in melanoma and cancer is not mandatory. Applicants with a strong history of non-cancer Immunology, Dermatology, Genomics, or other cancer biology are strongly encouraged to apply.
- Familiarity with programming languages such as Python or R, and experience with working with large datasets will be highly advantageous. However, candidates with the right Immunological experience but without computational background will have opportunity to be specifically trained in proprietary and in-house programmatic development with robust bioinformatics didactics available.
- Applicants from underrepresented groups are strongly encouraged to apply.
- Applicants are not limited to United States citizens.
We welcome you to apply if you are dedicated, collaborative, and eager to drive scientific discovery and innovation. Stanford University and Stanford School of Medicine are committed to fostering scientific growth and you will be pivotal in contributing to our mission of discovery and translating research into clinical practice.
1. Cover letter that describes your research interests and background
2. Current CV with publication list
3. Contact information for three references