Our Research Laboratories’ Postdoctoral Research Fellow Program aims to be a best-in-industry program for industrial postdoctoral researchers, designed to provide you with an academic focus in a commercial environment. With the resources, reach, and expertise of a large pharmaceutical company, postdoctoral researchers will be positioned to excel in an institution committed to breakthrough innovation in research and discovery.

As part of our goal to promote basic research that will support future therapeutic development, we seek a motivated post-doctoral fellow to perform a tissue-based research project focused on stromal biology in cancer. The candidate will assume a highly interdisciplinary position at the intersection of pathology, oncology, and applied computer science within the Anatomic Pathology Group at our Research & Development Division South San Francisco.   

As a post-doctoral fellow, you will leverage an existing dataset on a human colon cancer cohort to explore the spatial dynamics of tumor and stromal cells. This unique position combines tissue-based assays (IF and multiplex imaging) and spatial transcriptomics analysis. Experience in IHC, IF, or multiplex imaging (Vectra, MIBI, CyCIF, CODEX) and image analysis is strongly desired. You will learn to utilize image analysis tools or work with open-source methods to perform custom analyses. Hence, experience with programming (PyTHON, R, or MATLAB) would be particularly valuable. As part of our initiative to automate pathology analytics, you will also interact with a team of machine-learning engineers developing deep-learning models for correlations of tumor microenvironment features with molecular data.  You will develop your scientific career in a dynamic network of pathologists, biologists, and bioinformaticians within industry.

The Successful Candidate will:

• Develop tissue-based assays (IF, multiplex IF, and CODEX) for tumor stromal cell subsets
• Analyze the spatial characteristics of the colon cancer microenvironment using spatial transcriptomics and multiplex imaging data 
• Perform statistical analysis on imaging data to find correlations with other clinical or molecular signatures  
• Leverage machine-learning tools to perform image analysis and identify image-based biomarkers
• Interact smoothly with pathologists, pathology bench scientists, statisticians, biologists, computer scientists, and informatics/IT staff, both internally and externally 
• Present data in internal and external venues
• Write manuscripts for publication.

This position will require a strong background in biology and in conducting scientific experiments. It will require a high level of curiosity and self-motivation to stay current with relevant knowledge in the field, high levels of creativity, an urge to experiment with new methods and technology, and a collaborative approach to science.