The Harvard Medical School (HMS) Laboratory of Systems Pharmacology (LSP) and Women’s Cancer Program at Dana-Farber Cancer Institute (DFCI) seeks an outstanding postdoctoral fellow who will use innovative single-cell methods to study mechanisms of immunotherapy response and resistance in patient tumors. The fellow will be based in the laboratories of Dr. Peter Sorger at HMS and Dr. Beth Mittendorf at DFCI, where he/she will routinely interact with physicians, basic scientists and computational biologists to conduct high impact translational research. The fellow’s research efforts will directly inform the design of novel clinical trials of immunotherapy for breast and ovarian cancer.
The fellow will lead efforts to apply single cell genomics and imaging, including a new tissue-based, multiplexed immunofluorescence assay (tCyCIF: www.cycif.org) to study the tumor microenvironment in breast and ovarian tumors. The high-dimensional single cell data will be used to identify novel cell types, functional states and drug targets. Using tCyCIF, the candidate will design and optimize informative antibody panels, apply these panels to patient samples, analyze the data using high-dimensional and single cell analysis methods, and correlate these measurements with clinical outcomes. This work not only has the potential to identify mechanisms of immunotherapy response/resistance and relevant predictive biomarkers, but also generate insights for novel therapeutics and/or rational combinations of existing drugs.
The successful candidate will be expected to lead and develop independent projects, supervise technicians, and work effectively as part of a multi-disciplinary team to generate, analyze, and present data.
The successful candidate will have an MD and/or PhD and relevant experience in cancer immunology and/or breast or ovarian cancer research. Prior experience working with mouse or human tissues and mastery of basic molecular biology techniques and cell culture are required. Proficiency in fluorescence microscopy and/or single cell methods such as flow cytometry/CyTOF are also highly desirable. The candidate should have an interest in acquiring skills in image processing and analysis and use of computational pipelines to produce and analyze single-cell data. A general understanding of Matlab/Python and prior experience in working with mouse or human tissues, including familiarity with tissue processing and analysis as well as basic knowledge of standard IHC is preferred. Excellent written and spoken English are required.
This position has no teaching or administrative duties.
Schedule: Full time, flexible. The hours of this position will vary to meet deadlines to complete experiments and achieve project goals in a timely fashion.
Please note that applicants must provide a CV and cover letter detailing their interest in the position and the relevance of their background and skills. Selected candidates will be asked to provide letters of reference.