We are seeking to hire a postdoctoral associate to join the Analytical and Translational Genomics Unit (ATGU) of Massachusetts General Hospital (MGH) in the research environment of Dr. Mark Daly, Dr. Hilary Finucane, Dr. Benjamin Neale and Dr. Ramnik Xavier. In this role, the postdoc will lead the interpretation of multimodal biological datasets to inform how genetic variants implicated in GWAS contribute to the etiology of, primarily, autoimmune disorders. The candidate should have a strong computational background and knowledge of statistical methods, as well as demonstrated expertise in large scale data processing and analysis, and be motivated to leverage genomics to understand disease pathology.

Dr. Daly is the Director of the ATGU and he co-directs the Broad Institute’s Medical and Population Genetics program along with co-director Dr. Finucane, who is a faculty member of Harvard Medical School (HMS). Dr. Neale is an Institute Member at the Broad Institute, Director of the Stanley Center’s Genetics program and the Director of the Genomics of Public Health Initiative (GePHI) at MGH and Harvard Medical School. Dr. Xavier is a Core Member of the Broad Institute, Director of the Klarman Cell observatory and Director of the Immunology Program. These four labs work collaboratively to devise and apply novel statistical methods for large scale genetic data to gain insight in to the epidemiology and biological mechanisms of complex traits, diseases and disorders.

The postdoctoral trainee will benefit from frequent and varied educational and skill-building opportunities both within the unit and through the Broad Institute more widely. We are highly engaged in the Broad’s Stanley Center for Psychiatric Research and the Medical and Population Genetics community, and we maintain close ties with scientific communities at MIT- and Harvard-based institutions, and collaborators across the world. The Broad Institute itself is a vibrant research environment and provides the potential for your contributions to be used and recognized worldwide.

A successful candidate is expected to excel at critical thinking and be a keen learner for new computational tools and analytical approaches. The postdoctoral trainee should be self-motivated and willing to take advantage of the multidisciplinary network of scientists around them and engage with collaborators and fellow group members.  

Characteristic Duties:

• The overarching goal of the postdoctoral research project will be to leverage multimodal biological datasets to understand how genetic variants implicated in GWAS contribute to the etiology of, primarily, autoimmune disorders.
• Utilize data derived from CRISPR-I and CRISPR-A experiments to learn the consequences on cellular phenotypes of genetic variants.
• Leverage cellular phenotypes in single cell expression and apply appropriate statistical tools to examine cellular variation.
• Develop a computational pipeline that performs efficient and reproducible analysis, including quality control measures.
• Employ cloud computing resources to perform distributed analyses at scale, through the development of reproducible and well-organized code.
• Create scientifically rigorous visualizations, communications, and presentations of results.
• Present results to a variety of audiences, including geneticists, molecular and cell biologists. 
• Opportunity to hone teaching and mentoring skills by overseeing junior team members.

All Broad employees, regardless of work location, must be fully vaccinated for COVID-19 by Tuesday, October 12, 2021. Requests for exemption for medical or sincerely held religious beliefs will be considered.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

Requirements:

• PhD in statistics, mathematics, genetics, bioinformatics or a closely related field, with solid training in analytical methods.
• Excellent computational/programming and analytical skills.
• Fast learner and analytical thinker, comfortable taking initiative to learn new skills and drive projects to completion.
• Demonstrated experience in statistical research and/or genetics, publication in scientific journals and demonstrated ability to communicate scientific ideas through verbal presentations.
• Motivation to communicate research findings with the broader field through high-quality publications.
• Strong communication skills and willingness to engage with other members of the lab and contribute ideas through team meetings and discussions.

Not required, but preferred qualifications:

• Submitted first-author or joint first-author papers in any of the project relevant fields. 
• Demonstrated proficiency in some common programming languages: Python, Perl, Unix, Java, Matlab, R, C, and C++. 
• Familiarity with using a HPC compute cluster and linux system.
• Experience in the analysis of large-scale genetic data sets a plus.