Career Center

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.