The Broad Institute of MIT and Harvard is seeking an outstanding candidate for a Computational Associate II position focused on developing novel liquid biopsy assays for cancer detection and monitoring based on circulating tumor DNA (ctDNA) within the Gerstner Center for Cancer Diagnostics and Broad Cancer Program. The Gerstner Center aims to develop blood biopsies, among other cancer diagnostics, that stand to benefit millions of patients worldwide.
The successful candidate will be principally responsible for implementing, optimizing, and applying bioinformatics workflows to advance new technology development and the application of novel diagnostic assays to impactful clinical studies.
The incumbent is expected to interface closely with a multidisciplinary team, performing analyses that directly inform (i) new experiments in the lab, (ii) new ways to apply our technologies, and (iii) new insights as to the predictive and prognostic power of our technologies in clinical studies, seeking to improve patient care. This exciting position affords the opportunity to join a multidisciplinary team of scientists, engineers, medical oncologists, and computational biologists, spanning the Broad Institute, MIT, Harvard, and Harvard-affiliated hospitals. The successful incumbent will gain exposure to cutting-edge science through meetings, symposia, and interactions with colleagues and collaborators, and have the opportunity to establish impactful new methods.
CHARACTERISTIC DUTIES
- Implements, optimizes, and applies novel bioinformatics methods for cancer detection and monitoring
- Works with lab members to design, conduct, analyze, and troubleshoot experiments
- Presents routinely at lab meetings to share project updates and discuss new ideas
- Assists in the preparation of manuscripts to report findings to the broader community
- Other related tasks as required
QUALIFICATIONS
- B.S. in Bioinformatics, Computational Biology, Computer Science, or related field and a minimum of 2+ years of related experience, or M.S. with 0+ years of experience; or equivalent work experience.
- Proficiency in R or Python required
- Practical experience with Unix / Linux environment required
- Experience with WDL/Cromwell or Snakemake workflow management systems preferred
- Experience with cloud computing platforms such as Google Cloud Platform preferred
- Experience with DNA sequencing and familiarity with molecular biology preferred
- Experience with epigenetic sequencing methods such as bisulfite, EM-Seq, or TAPS preferred
- Experience with Duplex Sequencing and cell-free RNA sequencing preferred
- Experience with developing and validating cancer detection algorithms preferred
- Excellent communication and interpersonal skills required
- Ability to work in a fast-paced, academic environment
