Postdoctoral Research Associate, Biological Data Science
Informatics | San Francisco, Ca | Temporary and Internship
Overview of the Role
The Postdoctoral Research Associate will leverage their scientific and/or computational expertise to make new discoveries that drive the development of new immunotherapies and increase our understanding of the mechanisms of action and resistance for current ones.
The Postdoctoral Research Associate is a training role, and during their time here the candidate will receive mentoring from Parker Institute researchers in cancer biology, immunology, bioinformatics, and/or machine learning, based on their interests and background. Candidates will also get opportunities to work with and learn from many of the leading immunotherapy researchers in the world, who serve as Parker Institute staff, as investigators at a Parker Institute affiliated site or as researchers at one of our industry partners.
Reporting Structure and Team
The Postdoctoral Reasearch Associate reports to the VP, Informatics and is a key member of the Informatics team.
Essential Job Functions
- Perform translationally-relevant research on the tumor-immune interface in collaboration with biological data scientists at the Parker Institute and researchers at PICI member labs
- Develop bioinformatics methods to analyze one or more of the 10+ data types we work with, including CyTOF, MIBI, 16S Ribosomal Sequencing, (single cell) ATAC-seq, Whole Exome Sequencing and (single cell) RNA-seq
- Leverage a cloud-based compute environment based around tools such as Docker, Cromwell/WDL, Google Cloud Platform, and deep learning frameworks such as Tensorflow, to perform rigorous, reproducible analysis on large data sets.
- Contribute to the scientific environment at the Parker Institute by presenting at internal meetings, identifying relevant literature, and broadly serving as an in-house expert on your research area.
- Publish in top-tier journals, contribute to open source projects, and/or present at national conferences, as desired.
Knowledge, Skills, and Experience
- Complete their Ph.D. in immunology, cancer biology, applied math, biophysics, bioinformatics, machine learning, computer science, or similar by start of fellowship
- Have solid data analysis abilities in R or Python
- Have a passion for collaborative, interdisciplinary scientific research that generates real impact
- Be highly motivated and able to work independently
- Have excellent oral and written communication skills
- Desired career path is not a criterion for selection, and candidates seeking to ultimately become industry data scientists, faculty members, start-up founders, or something else altogether are encouraged to apply.