Post Mon Jan 20, 2020 6:01 pm

Postdoctoral Position Stanford University

The Fantl Lab at Stanford University School of Medicine studies human tumors with translational endpoints with the over-arching goal to dramatically shorten the time from bench to bedside. We use multi-parameter single cell technologies (CyTOF and multiplex imaging) to comprehensively characterize human tumors on a cell-by-cell basis; specifically ovarian, kidney and prostate. Two areas of focus of the lab are tumor-immune interactions and the DNA-damage response. To date, work from our and other labs have demonstrated that multi-parameter single cell technologies have provided an unprecedented level of mechanistic detail not only revealing further unappreciated complexity of tumor ecosystems, but directing us toward more meaningful novel biomarkers. These are highly likely to guide far more beneficial treatment regimens for cancer patients. We work collaboratively in multidisciplinary teams. We synergize with bioinformaticians for integrating large data-sets and clinicians to ensure the acquisition of tumor tissue and also to keep us on track as to what will make a difference to patients.
The Fantl Lab is seeking a highly motivated and creative postdoctoral fellow to study one or more of several projects. The candidate will perform CyTOF combined with imaging, genomic and RNA-Seq experiments in clinically annotated tumors and use integrative computational tools to provide novel insight about disease mechanism and develop potential biomarkers. Proposed projects include, but are not limited to: i) therapeutic resistance in ovarian cancer ii) predictive biomarkers for women with ovarian cancer likely to respond to PARPis iii) understanding the role of BRCA1/2 with the tumor immune infiltrate in ovarian cancer iv) predicting response of renal cell carcinoma patients to immunotherapy v) determining which men with localized prostate cancer will develop aggressive disease.
Educational Requirements:
PhD Biological Sciences, Immunology (knowledge of flow and mass cytometry), Computer Science, Bioinformatics, Molecular Biology, Genetics, and/or related field of study.
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