The Pinello Lab at Harvard Medical School/Massachusetts General Hospital/Broad Institute of MIT and Harvard is looking for Research Scientists/Postdoctoral Candidates/ Computational Biologists and Programmers excited about computational challenges in modeling biological data coming from CRISPR genome editing, chromatin biology and single-cell experiments.
Massachusetts General Hospital is a teaching hospital for Harvard Medical School and one of the top ranked hospitals nationwide. We are located in Boston, Massachusetts with close proximity to numerous other top-notch medical and research institutions including Harvard School of Public Health, Massachusetts Institute of Technology (MIT), The Broad Institute of MIT and Harvard, Boston Children’s Hospital, 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 focus of the Pinello laboratory is to use innovative computational approaches and cutting-edge experimental assays to systematically analyze sources of genetic and epigenetic variation and gene expression variability that underlie human traits and diseases. The 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. Our mission is to use computational strategies to further our understanding of gene regulation in development and disease etiology and to provide a foundation for the development of new drugs and more targeted treatments.
The candidate(s) will work on projects developing innovative computational approaches to design and systematically analyze bulk and single-cell CRISPR perturbation experiments and integrate transcriptome, epigenome, proteome, and genome structural datasets to investigate how genetic variants and regulatory elements control gene expression and phenotypes at an unprecedented scale.
One major activity will be to contribute to the recently NIH funded Impact of Genomic Variation on Function (IGVF) consortium: www.genome.gov/Funded-Programs-Projects/Impact-of-Genomic-Variation-on-Function-Consortium. Our group recently joined this consortium, and it is funded for 5 years to work with other investigators to understand how genomic variation alters human genome function, and how such variation influences human health and disease.
Read more about our research, recent publications, and software here: pinellolab.org
- 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
- Strong statistical background and preferably statistical genetics background
- Experience with commonly used bioinformatics tools and databases
- Experience working with different types of NGS data such as ChIP-seq, RNA-seq, ATAC-seq
- Knowledge of commonly-used machine learning methods
- Experience in the analysis of single cell data and genome editing data
- Experience in developing computational pipelines with Snakemake or Nextflow
- Web development
Our lab is 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: email@example.com.