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About the Role

This role focuses on the intersection of cardiovascular disease and human genetics, utilizing both classical bioinformatics and deep learning techniques. The incumbent will manage, clean, and analyze large-scale medical data, maintain bioinformatic databases, and develop analytic pipelines to support research discovery and replication.

Responsibilities

• Develop and utilize computational tools to analyze biological research data.
• Design experiments and build machine learning and statistical models.
• Implement end-user needs in database development, maintenance, and integration.
• Manage cloud and on-premises computational infrastructure.
• Track the flow of samples and information for large-scale studies.
• Provide access to public and proprietary databases.
• Clean and analyze large-scale medical data.
• Maintain bioinformatic databases by restructuring proprietary and public data.
• Write tools to streamline discovery and replication analyses.
• Develop and maintain analytic pipelines.
• Perform bioinformatic analyses including variant calling and annotation.
• Perform administrative duties.
• Participate in and lead authorship teams.

Requirements

• Strong foundation in computer programming.
• Ability to learn and implement new techniques.
• Experience with databases or willingness to learn.
• Comfortable with bioinformatic analyses.

Skills

• R
• Python
• Go
• Rust
• Shell
• SQL
• WDL
• Docker
• AWS
• Microsoft Azure
• Google Cloud
• Machine learning
• Statistical modeling
• Variant calling
• Annotation
• Deep learning

Experience Level

• Professional with experience applying job skills to projects of moderate scope and complexity.