Postdoctoral Fellow - Cardiovascular Disease Initiative CVDi
Postdoctoral Fellow - Cardiovascular Disease Initiative CVDi
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Job Description
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Description & Requirements
The Broad Institute is an amazing place we apply our deep knowledge of human genetics to empower a revolution in biomedicine and accelerate the pace at which the world conquers disease. Through our partnerships with MIT Harvard and the Harvard teaching hospitals weve become a worldwide hub of cuttingedge biomedical science. The Broad was founded to explore the applications of genomic medicine and now conducts research in infectious disease cancer and inherited disease along with basic research in the life sciences.
The Broad is looking for an exceptional postdoctoral fellow candidate to join the Ellinor laboratory within the Cardiovascular Disease Initiative (CVDi). The successful candidate will join an interdisciplinary team of computational scientists machine learning scientists laboratory scientists and clinicians working together to further understand the underlying causes of cardiac diseases and contribute to identifying and validating new molecular targets in the field.
This role is anticipated to bridge clinical science and population genetics of cardiovascular disease. The ideal candidate would carry out both analysis of large scale genetic and clinical datasets. They should be facile executing analyses of genotypearray and genomesequencing. In addition a focus area will be the application of modern machine learning techniques to clinical imaging data sets such as electrocardiograms or magnetic resonance imaging.
The candidate would collaborate directly with other postdoctoral fellows and scientists performing experimental research studies at the bench. They will be contributing to and leading the writing of scientific manuscripts and working within international collaborations and potentially with industry partners.
Example work streams may include:
Design and lead independent analytical projects
Run genomewide association studies on genotype array data and genomesequencing data
Analyze genomic and phenotypic data from the AFGen Consortium and large biobanks such as UK Biobank All of Us and the Million Veterans Program
Perform downstream analyses with GWAS summary level results including polygenic risks scores expression quantitative trait loci transcriptomewide association studies enrichment analyses LD score regression and gene prioritization methods
Integrate genomics data with other available expression sequencing and epigenetic datasets to help prioritize potential therapeutic targets
Perform clinical and epidemiological studies of cardiovascular disease.
Collaborate with machine learning scientists to apply stateoftheart deep learning models for exact phenotyping.
Work in an interdisciplinary team contributing to study designs in collaboration with clinicians and data scientists
Mentor junior computational lab members
Create scientifically rigorous visualizations communications and presentations of results
Prepare scientific manuscripts contribute to writing grants
Help to maintain and organize computational infrastructure and resources
Contribute to generation of protocols and intellectual property
Requirements:
MD with clinical/epidemiological/genetic research experience or Ph.D. in a quantitative discipline such as computational biology computer science bioinformatics statistics mathematics physics or related field preferred but talented applicants of all levels are encouraged to apply
Demonstrated expertise in genomics data analysis and enthusiasm about biology technology and cardiovascular medicine
Experience with standard bioinformatics tools and Python R or an equivalent scripting language.
Experience with either high performance computing environments or cloud based computational environments (Google Cloud AWS Azure) is preferred
Experience performing genomewide association studies (single variant and gene based tests) and quality control procedures for variant and sample filtering is a plus
Track record of working on complex problems and ability to integrate data from multiple disciplines
Strong interpersonal influencing and collaboration skills to work in a teamoriented matrix environment
Outstanding personal initiative communication skills and the ability to work effectively as part of a team
Outstanding verbal and written communication abilities
A passion for science and sense of urgency to find new medicines to benefit patients
Employment Type
Grant
