Bioinformaticist in Human Genetics and Functional Genomics of Eye Disease

Massachusetts Eye and Ear, Harvard Medical School
United States MA Boston


We are seeking a highly qualified and motivated Bioinformaticist or computational biologist to join our collaborative teams in the Ocular Genomics Institute and the Department of Ophthalmology at Massachusetts Eye and Ear (MEE), Harvard Medical School, to work on innovative projects that combine human genetics, functional genomics, and systems biology approaches to uncover novel causal mechanisms and improve diagnostics of rare and common eye diseases, including glaucoma and inherited retinal degeneration.

The successful candidate should have a MSc or PhD in bioinformatics, computational biology, biostatistics, computer science, or a related quantitative field, and will be interested to apply and develop computational and statistical methods for analyzing sequencing data, large-scale genotype-phenotype association studies, and functional genomics data. The ideal candidate will have strong programming skills, a solid statistical understanding, and experience with large-scale data analysis, and will be excited to contribute to advancing the scientific discovery and medicine of eye disease.

The candidate will work with the Rossin, Segrè, and Wiggs labs that are part of a vibrant research community of computational biologists, experimentalists and clinician scientists in the Ocular Genomics Institute at MEE, an international leader for treatment and research in Ophthalmology and Otolaryngology. The labs are affiliated with the Medical and Population Genetics community at the Broad Institute of Harvard and MIT. Being a member of our group will provide the opportunity to contribute to impactful projects and large collaborative efforts in the field of genomics and human disease. To learn more about our lab research directions please visit: and

• Perform preprocessing and quality control of genotype array, whole exome and whole genome sequencing data, using existing and custom-built tools on a local HPC cluster and cloud-based environment.
• Perform association testing of common and rare variants in whole exome and whole genome sequencing data from cohorts of early and late-onset glaucoma and controls, and from Biobank studies.
• Build polygenic risk scores in large genotype-phenotype studies of glaucoma and test for association with various clinical features to help translate genetic discoveries into personalized approaches for disease diagnosis and treatment.
• Perform structure-based network analysis on mutations in rare inherited retinal degeneration genes and apply to patient sequencing data to identify and distinguish causal variants from neutral ones using a pre-existing pipeline built in Python and R.
• Help optimize the code for the structure-based network analysis pipeline using benchmark data
• Organize all scripts in a publicly available repository (e.g., github) with clear documentation.
• Critically review, analyze, and communicate results to our team and collaborators.
• Candidate will work both on independent and collaborative projects, and will summarize work for publications.


• M.Sc. or Ph.D. in bioinformatics, computational biology, computer science, (bio)statistics, mathematics, or a related quantitative discipline required.
• Strong programming skills and in-depth experience with several programming languages required, e.g. Python, R, C++; Experience with Cloud Computing a plus.
• Experience with Unix/Linux environments, including shell scripting, is required.
• Research experience with large-scale data analysis, such next-generation sequencing, algorithm development and statistics required.
• Background in statistical genetics, computational genomics, or machine learning is a plus.
• Motivation to contribute to genomic research of eye disease is essential.
• Demonstrate critical thinking, rigorous work, and ability to meet deadlines.
• Strong personal skills, and excellent organization and verbal and written communication skills.
• Ability to work effectively both independently and collaboratively in a fast-paced, academic environment and evolving field.

Start date

As soon as possible

How to Apply

Please send your CV, a cover letter describing your previous research experience and future research interests, and contact information for 3 references, to Dr. Ayellet Segrè: ayellet_segre [at], Dr. Lizzy Rossin: Elizabeth_Rossin [at], and Dr. Janey Wiggs: Janey_Wiggs [at]