Job description
Job Description
Apply your computational and mathematical skills to solving the hardest problems in big-data genomics and have a wide impact on science and clinical practice, including diabetes and related cardiometabolic traits. Join a team co-mentored by two investigators (Dr. Josep Maria Mercader, a statistical geneticist at the Broad Institute, and Dr. Aaron Leong, an endocrinologist at Massachusetts General Hospital) as Computational Associate I to support the development of new methodologies to unravel the genetic basis of type 2 diabetes and its application to healthcare analytics and precision medicine.
This position will be as a member of the Mercader – Leong team,part of the Jose Florez lab (https://florezlab.mgh.harvard.edu/), which generates and analyzes large scale genetic datasets to illuminate the causal pathways of type 2 diabetes and to identify novel therapeutic targets. Our research group aims to understand how genetic variation, or their associated molecular defect, affect human physiology and diabetes risk. We thus seek to characterize the glycemic, hormonal and metabolomic responses to the dietary and pharmacological perturbations according to genotype. The analyst will analyze genetic and electronic health records data from large-scale biobanks, including the Mass General Brigham Biobank, UK Biobank, All of Us Research Program data, and others. The candidate will participate in the curation of electronic health records datasets, perform quality control and genetic association analyses, and analyze multi-omics data using machine learning techniques for the prediction of health outcomes within these biobanks. The analyst will provide analytic support to analyze gene expression data from diabetes relevant tissues from non-European populations, funded by two projects from the American Diabetes Association.
The position will be also funded by a U01 grant to develop and Polygenic Risk Scores (PRS) for Diabetes and Complications across the Life-Span in Populations of Diverse Ancestry (https://primedconsortium.org/). This project will contribute to address the disparities in PRS across ancestries, we have assembled a multi-disciplinary team to aggregate and analyze the largest existing genetic data from more than 1.8 M individuals (35% non-European) with T1D, T2D, GDM and glycemia-related complications and quantitative traits to improve the PRS prediction of diabetes and progression across the lifespan in diverse ancestries.
The Computational Associate I will be primarily based at the Broad Institute and spend up to 50% of the time at Massachusetts General Hospital. The Broad is a research institution affiliated with Massachusetts Institute of Technology and Harvard University that is transforming medicine and human health by building software to organize, process, and visualize scientific data on an unprecedented scale. The candidate will be part of the Medical and Population Genetics program, Metabolism Program, and the broader Diabetes Research Group at the Broad Institute. The position will involve close interaction with team members and collaborators across the Diabetes Research Group, the Medical and Population Genetics, and the Metabolism the Broad Institute. At the MGH our group conducts clinical studies to understand the physiological consequences of genetic variants associated with diabetes or other glycemic traits or those individuals at the extreme of polygenic risk scores.
OVERALL RESPONSIBILITY The successful candidate will have experience in analytical pipelines and tools, the generation polygenic scores for various traits, the curation of phenotypes within electronic heath records for longitudinal prediction, and large-scale human disease datasets. The candidate will also identify participants eligible for recruitment in recall-by-genotype studies and will analyze a variety of pharmacogenomic and physiological omics data derived from the clinical studies.
PRINCIPAL DUTIES AND RESPONSIBILITIES (*Essential Functions) * Work closely with experts in performing genetic analyses and analyzing electronic health records. Works closely with research coordinators and clinicians to help design and analyze the resulting clinical data. The candidate must apply proficiency with analysis software, diagnose and resolve user issues, and provide scientific/technical support. Perform statistical analyses of disease association, across large-scale datasets. Experience with statistical analysis software with R, coding and Unix expertise and familiarity with job scheduling in a cluster and/or cloud computing will be required.
QUALIFICATIONS
B.A.in bioinformatics, biology, statistics, data science, machine learning, computer science, or a related field, or equivalent practical experience
General knowledge of statistical methods for genomic data analysis
Fluency in Unix, standard bioinformatics tools (Python, R, or equivalent).
Experience with cloud-based computational environments desirable
Excellent communication, organization, and time management skills
Creative, organized, motivated, team player
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.
EEO is The Law - click here for more information
Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled
Check out this video for a look into our community!
smogtown13.com is the go-to platform for job seekers looking for the best job postings from around the web. With a focus on quality, the platform guarantees that all job postings are from reliable sources and are up-to-date. It also offers a variety of tools to help users find the perfect job for them, such as searching by location and filtering by industry. Furthermore, smogtown13.com provides helpful resources like resume tips and career advice to give job seekers an edge in their search. With its commitment to quality and user-friendliness, smogtown13.com is the ideal place to find your next job.