The Stanford Center for Cancer Systems Biology (CCSB) aims to identify mechanisms by which cancer cells “teach” the immune system to tolerate them, with a focus on little-studied interactions in lymph nodes, which are a frequent precursor to wider metastasis. We are analyzing cancer-immune interactions with a variety of high-throughput assays including RNA-seq and single-cell imaging.
The Gentles lab has an opening for a postdoctoral fellow to analyze genomic data in relation to treatment response and survival outcomes (see for example precog.stanford.edu). The overall aim of the project is to develop and apply methods for identifying biomarkers and processes involved in lymph node and distant metastasis, initially focusing on public datasets, and extending to our own RNA-seq and other data. A key hypothesis of our center is that immune tolerance permitting distant metastasis is mediated by interactions that occur in lymph nodes, which are being studied in the Engleman lab with mouse models. We have a specific focus on melanoma, and head and neck squamous cell carcinomas.
Stanford has many opportunities for career development such as grant and paper writing workshops, entrepreneurial programs, and the ability to audit a wide variety of courses.
Further information about the Center and scientific aims can be found at ccsb.stanford.edu.
Stanford University is an affirmative action and equal opportunity employer, committed to increasing the diversity of its workforce. It welcomes applications from women, members of minority groups, veterans, persons with disabilities, and others who would bring additional dimensions to the university's research and teaching mission.
Candidates should have, or be close to completing, a Ph.D. in computational biology, bioinformatics, biostatistics, or a related field; and should not have more than 3 years of postdoctoral experience. Strong computational skills as well as knowledge of machine learning and prediction methods are essential, as is a genuine interest in the scientific questions being investigated in the Center. Experience with a programming language suitable for biostatistical analysis (such as R or Python) is required, and UNIX/Linux cluster computing experience is recommended. Experience with genomic analyses (microarray analyses, RNAseq analyses) is strongly preferred; integration of large data sets, and analyses of multiple types of omics data would all be valuable assets.
The candidate should have strong written and verbal English skills, communication and interpersonal skills. You will be working closely with experimental and clinical collaborators, so should be willing to communicate across disciplinary boundaries and take the initiative in projects. Attention to detail and ability to work on multiple projects are important.
Please submit a CV, brief statement of interest, and names of at least two references by email to Andrew Gentles: andrew DOT gentles AT stanford.edu