Postdoctoral Associate - Xavier Lab - 40524

Broad Institute
United States, Massachusetts, Cambridge
Jan 03, 2025
Description & Requirements The Broad The Broad Institute of MIT and Harvard is one of the world's leading biomedical research institutes. It seeks to discover the molecular basis of major human diseases, develop effective new approaches to diagnostics and therapeutics, and disseminate discoveries, tools, methods, and data openly to the entire scientific community. Founded in 2004, the Broad Institute includes faculty, professional staff, and students from throughout the MIT and Harvard biomedical research communities, with collaborations spanning the globe. The lab We are seeking to hire a postdoctoral associate to join the Broad Institute and Massachusetts General Hospital to be mentored by Ramnik Xavier (rxavier@broadinstitute.org). In this role, the postdoc will lead the development and application of novel methods for the integration of multimodal biological datasets to understand how common and rare variants associated to autoimmune disease and neurodegenerative disease contribute to etiology. 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. 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. Job responsibilities The overarching goal of the postdoctoral research project will be to leverage multimodal biological datasets to understand how rare and common genetic associations contribute to the etiology. 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. Minimum qualifications PhD in statistics, mathematics, genetics, bioinformatics or a closely related field, with solid training in analytical methods. Excellent computational/programming and analytical skills. Demonstrated experience in statistical research and/or genetics, publication in scientific journals and demonstrated ability to communicate scientific ideas through verbal presentations.