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Postdoctoral Associate, Computational Cancer Biology (23599931370109)

Tracking Code: 23599931370109

Job Description
We are looking for post-doctoral fellows with expertise and interest in Computational Biology/Bioinformatics and Cancer Multi-Omics, to work in a multi-disciplinary research group studying the pathobiology causes of cancer, with a particular focus on breast and head and neck cancer. The fellows would join Dr. Stefano Monti's lab and a multi-disciplinary team at BU Schools of Medicine, Dental Medicine, and Public Health, and Tufts Medical Center, that focuses on studying the mechanisms of tumor initiation and progression and how these may be affected by environmental exposure.

The fellows' responsibility would include the analysis and integration of data from multiple assays, including high-throughput bulk and single cell sequencing (RNAseq, DNAseq), methylomics, and proteomics data. To this end, expert application of existing computational methodologies (clustering, regression and classification, gene regulatory network inference, etc.) and development of new systems biology approaches will both be needed. The overarching goal is the elucidation of the biological mechanisms driving malignant transformation and immune checkpoints to improve cancer interception. Publicly available and in-house generated data from primary tissues, model organisms and 2D/3D cell cultures will be leveraged toward this goal.

Within this broad focus, there will be opportunities for the candidate to develop their own research project. Importantly, the fellow will join the Section of Computational Biomedicine at BU School of Medicine (BUSM), which functions as a highly collaborative environment, where faculty and trainees from the different labs share the working space as well as a research philosophy deeply rooted in the adoption of the modern tools of multi-omics biology and the associated data interpretation methods.

The ideal candidates 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.


Required Skills
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, familiarity with GitHub, Docker, and Unix systems, knowledge of database management and other programming languages a plus.
• Demonstrated biostatistics, applied bioinformatics/computational proficiency as evidenced by relevant publications in peer-reviewed journals.
• Demonstrated knowledge and use of publicly available omics 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.

These positions will be supported through NIH/NCI/NIDCR R01/U01 funding, and 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

& Bioinformatics Program

Email: montilab@bu.edu

David Sherr, Ph.D.

School of Public Health

Boston University

Email: dsherr@bu.edu

Please note all newly hired staff and faculty will need to be in compliance with Boston Universitys 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 Universitys 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.

#LI-DNP


Job Location: Boston, Massachusetts, United States
Position Type: Full-Time/Regular
Salary Grade: Competitive

To apply, visit https://bu.silkroad.com/epostings/submit.cfm?fuseaction=app.jobinfo&jobid=311410&company_id=15509&version=1&source=ONLINE&jobOwner=1016383&aid=1







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