gastrointestinal cancers and pre-malignant lesions, including in the context of neoadjuvant therapies. This pipeline has generated a multimodal immune profiling dataset of cancer patients treated with immunotherapy, including flow cytometry, scRNA-seq, spatial transcriptomics, and co-registered multiplex immunofluorescence (mIF) and H&E whole-slide images, all linked to comprehensive clinical annotations. This is complemented with mechanistic mouse models to functionally establish immune and tumor co-evolutionary networks in gastric tumors, tumor draining lymph nodes and metastases. We are seeking highly motivated candidates with advanced computational biology skills in the technical areas of single cell and spatial omics, ideally with some background or advanced knowledge of tumor immunology. The position is funded by a 5yr R01 newly awarded to our investigator group.
The successful candidate will have the opportunity to lead the science for integrating multimodal datasets addressing fundamental unanswered questions in gastric cancer biology, and addressing the urgent clinical unmet need plaguing patients afflicted with gastric cancer. The fellow will work closely with, and will be mentored by, world-leading experts in computational oncology, immunology, pathology, GI oncology&surgery, with opportunities to develop both methodological innovations and lead discovery-based research.
Profiles of the co-mentors of this role are listed below:
Key Requirements
Hold a Ph.D. in biostatistics, statistics, computer science, computational biology, or related quantitative discipline. Have published a 1st author paper from PhD dissertation or postdoctoral research
Core Skills
PhD-level experience in computational biology, single cell omics applied in a cancer setting
- Experience in high-dimensional data analysis
- Preferably have advanced knowledge of topics in tumor biology and immunology
Submit C.V., cover letter, and 3 references in your application submission to: Cristina Radu raduc@mskcc.org
Salary range $75,000 - $80,000 based on PGY level
