About the MacArthur Lab
We are a tight-knit research group jointly based as Massachusetts General Hospital and the Broad Institute of Harvard and MIT, and leveraging the largest genomic data sets in the world and cutting-edge analysis methods to make sense of human genetic variation. We’re committed to open data and open-source code, as well as experimenting with new methods of communication. Working with us is a chance to learn from experts in computational biology, large-scale genomics, variant interpretation, software development and clinical genomics, as well as to make a difference to the lives of hundreds of families affected by rare diseases.
Software Engineer: Rare Disease Genomics
Join a team that’s building open-source web-based decision support tools to dramatically accelerate the pace of diagnosis for families affected by rare genetic conditions. Our platform seqr (github.com/macarthur-lab/seqr) is used by an international consortium of collaborating clinicians, researchers, and industry partners, and significantly improves their ability to search through large genetic datasets and make discoveries and diagnoses. seqr is core to our efforts both in the Rare Genomes Project (raregenomes.org) and the Broad Center for Mendelian Genomics (cmg.broadinstitute.org), and has already enabled us to provide genetic diagnoses to more than 1,000 rare disease families. We are now looking for a full-stack software engineer that will help with the next phase of this project.
- BS or MS degree in Computer Science or other scientific discipline.
- Experience delivering clear, well-designed software.
- Interest in working with a wide variety of technologies and on diverse problems.
- Excellent communication skills and ability to work with users.
- Experience with Django, React.js, Redux, SQL, elasticsearch, Google Cloud Platform and Kubernetes is preferred.
- Familiarity with genomics and DNA sequencing data analysis is a plus.
Please apply via Broad Institute careers site.
We are looking for postdoc candidates with backgrounds in computational genomics or statistical genetics, ideally with direct experience in analyzing human sequencing data. Projects include identifying human knockouts, leveraging large human genetic data sets for drug target discovery, and improving the diagnosis of rare disease patients. Most importantly, we’re looking for people who are passionate about the translation of genomics into clinical practice, and have the right personality to work in a fast-paced and highly collaborative environment.
To apply, email Daniel with your CV.