Boston, Massachusetts
Northern & Central California, California
Charlottesville, Virginia
Los Angeles, California
Syracuse, New York
Brownsville, Texas
Los Angeles, California
New York, New York
St. Petersburg, Florida
Los Angeles, California
UMBC Shady Grove Campus, 9631 Gudelsky Drive, Rockville, MD 20850
The ideal candidate should have strong foundations in machine-learning and statistical algorithms to analyze genomic and phenotypic data from observational and experimental studies; experience in the experimental design and analysis of genomics studies; and a keen interest in following up on the biological leads the analyses will yield. The position would be for a minimum of 3 years with a possibility of 1-2 years renewal.
Requirements: Qualified candidates should have:
- A Ph.D. or equivalent degree in computational biology/bioinformatics, or related field.
- Ability to program in R/Rshiny and Python, with knowledge of database management and other programming languages a plus.
- Familiarity with Unix systems.
- Demonstrated biostatistics, applied bioinformatics/computational proficiency as evidenced by relevant publications in peer-reviewed journals.
- Demonstrated knowledge and use of publicly available data resources (TCGA, CPTAC, CCLE, GTEx, CMap, HTAN, etc.)
- Demonstrated understanding of cancer biology.
To apply: Submit an application including a statement of interest, a complete CV that includes details of training, research experiences, publications, and presentations at conferences, and contacts of 3 letter writers to
This position will be funded through the generous donations of Find the Cause Breast Cancer Foundation
Address inquiries to:
- Stefano Monti, Ph.D.
Section of Computational Biomedicine
Boston University School of Medicine
Email: montilab@bu.edu
- David Sherr, Ph.D.
Boston University
Email: dsherr@bu.edu
Please note all newly hired staff and faculty will need to be in compliance with Boston University's COVID-19 Vaccination and Booster Requirement within 30 days of date of hire. You must upload your vaccine documentation or request a medical or religious exemption (instructions). For further information on the University's response to COVID-19, please visit the COVID-19 Resources site.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, physical or mental disability, sexual orientation, gender identity, genetic information, military service, pregnancy or pregnancy-related condition, or because of marital, parental, or veteran status. We are a VEVRAA Federal Contractor.
