We are looking for a post-doctoral fellow with expertise and interest in Computational Biology/Bioinformatics, Cancer Multi-Omics, and Toxicogenomics, to work in a research consortium studying environmental causes of breast, oral, and lung cancer. The fellow would join a multi-disciplinary team at BU Schools of 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, primarily in Breast Cancer, but also in Head and Neck and Lung Cancer.

The fellow's 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 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.

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

& 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 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.

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