The Pinello and the Bauer Labs at Massachusetts General Hospital / Boston Children’s Hospital / Harvard Medical School are looking for Postdoctoral candidates excited about computational challenges in CRISPR genome editing, chromatin biology and single-cell analysis.
Massachusetts General Hospital is a teaching hospital for Harvard Medical School and one of the top ranked hospitals nationwide. Boston Children’s Hospital is one of the top pediatric research centers in the world, and a major research and teaching affiliate of Harvard Medical School. They are located in Boston, Massachusetts with close proximity to numerous other top-notch medical and research institutions including Harvard Medical School, Harvard School of Public Health, Massachusetts Institute of Technology (MIT), The Broad Institute of MIT and Harvard, Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Beth Israel Deaconess Medical Center, which fosters close interactions among faculty and fellows and a strong and rich network of collaborations and intellectual exchange.
The candidate(s) will work on projects developing innovative computational approaches to systematically analyze bulk and single-cell CRISPR perturbation experiments and integrate transcriptome, epigenome, proteome, and genome structural datasets to investigate gene regulatory networks.
The Pinello lab uses machine learning, data mining and high-performance computing technologies such as parallel and GPU computing to solve computationally challenging and Big Data problems associated with next generation sequencing (NGS) data analysis.
The Bauer lab develops and applies functional genomics methods to investigate gene regulatory mechanisms and networks that contribute to health and disease and to develop innovative therapeutics. The lab has identified favorable targets for therapeutic genome editing for the β-hemoglobinopathies, now being investigated in clinical trials; elucidated molecular mechanisms of hemoglobin switching; advanced high-throughput gene editing approaches to associate genetic variants with phenotypes; and developed methods for highly efficient and specific gene editing in human hematopoietic stem cells.
The ideal candidate(s) should have received (or expect to receive soon) a Ph.D. in Computer Science, Statistics, Genetics, Bioinformatics, Computational Biology, Mathematics, Physics, or related fields First (or co-first) author in one or more peer-reviewed scientific publication Excellent communication and writing skills Able to work both independently and in teams Preferred Skills (not required)
Proficiency in Python and/or R Experience with commonly used bioinformatics tools and databases Experience working with different types of NGS data such as ChIP-seq, RNA-seq, ATAC-seq Experience in the analysis of data from genome editing assays Experience in the analysis of single cell data and genome editing data Wet-lab experience Knowledge of commonly-used machine learning methods Web development
Our labs are committed to diversity and equality; therefore, we encourage applications from underrepresented minorities.
If you are interested, please send your CV and a cover letter describing your current and future research interests, and the contact of 3 references to Luca: firstname.lastname@example.org and Dan: email@example.com