Job Description

Apply your computational and statistical skills to analyzing exciting datasets and designing algorithms. This is a rare opportunity to be part of an exciting, collaborative team of clinicians, biochemists, cell and computational biologists that work together in Vamsi Mootha's laboratory to study mitochondria and their role in human disease.

About the Lab

The laboratory is affiliated with the Broad Institute, Harvard Systems Biology, Massachusetts General Hospital, and HHMI. It consists of a dynamic team of ~25 post-doctoral researchers, clinical fellows, graduate students and research scientists. The laboratory combines the latest tools of genomics,computation, and biochemical physiology to systematically investigate mitochondria- key organelles in our body that are crucial for energymetabolism and linked to rare diseases, neurodegenerative diseases such as Parkinson's disease, and aging. Our lab spans very basic biology and mechanisms to translational efforts aimed at alleviating disease. Recent work includes the development of new"big data"computational algorithms to predict gene function, discovery of new mitochondrial pathways, and the discovery that hypoxia (low oxygen) can profoundly improve the healthspan and lifespan of mouse models of mitochondrial disease. The collaborative environment between biologists and computational scientists provides excellent opportunities for high-impact research.

Job Description

As part of this job, you will work closely with post-doctoral fellows and senior computational biologists to analyze cutting-edge datasets - including metabolomics, proteomics, RNA sequencing, and whole genome sequences. You will design algorithms, apply statistical methods, innovate ways to visualize and interpret data - all toward solving exciting and medically-relevant problems. You will read and interpret scientific papers and contribute to high-profile publications. Background in computational biology or computational chemistry is strongly preferred.

Key Responsibilities

• Rapidly analyze and interpret new types of data
• Learn best-practices for analyzing many types of genomic data
• Work closely with biologists to interpret and validate exciting findings
• Prepare written reports and oral presentations for internal use and publication

Requirements

• M.S. or M.A. in Computational Biology, Bioinformatics, Computer Science, or Mathematics; or B.S. or B.A. in such subject areas and 2+ years of relevant research experience.
• Strong scientific programming background (e.g. Python, R, Julia)
• Coursework in Statistics and/or Data Science
• Excellent oral and written English communication skills
• Ability to solve complex problems
• Direct experience with analysis of "-omics" data sets is preferred, but not required.

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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.