The application materials should be emailed to email@example.com using the subject line “Postdoctoral position in the Fantl Lab.”
We have an exciting postdoc position for a highly motivated, creative, and committed postdoctoral fellow to study one or more of several projects related to ovarian and kidney cancer using multiparametric single cell approaches applied to human tissues.
The Fantl Lab in the Department of Urology at Stanford University School of Medicine studies human tumors, specifically ovarian and kidney, using mass cytometry/CyTOF and CODEX multiplex imaging. These cutting- edge multiparameter single cell technologies were developed at Stanford to address the well-established complexities associated with cellular heterogeneity in healthy and diseased tissues.
Our two main areas of interest are immune interactions and the DNA-damage response within the tumor micro-environment. To date, work from our and other labs have demonstrated that multi-parameter single cell technologies can provide an unprecedented level of mechanistic detail revealing previously unappreciated complexities between intra-tumoral cell types as well as the identification of novel biomarkers. Both have the potential to optimize existing treatment regimens for cancer patients as well as uncovering potential new therapeutic targets. We work collaboratively with computational biologists for integrating the large datasets generated with our technologies. Essential to our studies is the supply of high quality well annotated tumor samples and to this end we work collaboratively with clinicians who provide critical insight to inform the direction of our studies to maximize potential benefit for patients.
The successful candidate will apply CyTOF and CODEX multiplex imaging to clinically annotated tumors and/or blood samples and use integrated computational tools to provide novel insight into disease mechanisms and develop potential biomarkers. Projects will address understanding the tumor-immune-stromal microenvironment in both ovarian and kidney tumors with the overarching goal of understanding the underlying biology of these tumors. The resulting data will be used in the development of mechanistic biomarkers that can provide critical information about disease progression, predict response to therapeutics, especially immunotherapy, and provide data regarding therapeutic resistance in both malignancies.
- PhD or MD/PhD in Biological Sciences, Immunology, Cancer Biology, Molecular Biology, Genetics, or related field of study.
- Proven ability to work both independently and within a team.
- The candidate should be good at problem-solving, data analysis/interpretation and with the ability to gain proficiency in new technologies.
- The candidate should possess good communication skills, both written and oral (English), and is expected to be a good team player.
Skills and Desired Background:
- Flow cytometry, mass cytometry, imaging, processing clinical samples, primary cell culture, general techniques in molecular biology (cloning, q-rt-PCR, RNA-Seq).
- Proficiency in flow cytometry analysis software and analyzing “big data” with machine learning approaches.
- Personal statement
- Three letters of reccomendation