The Department of Medicine, Division of Cardiovascular Medicine is looking for a Bioinformatics Engineer / Data Scientist to join the Bioinformatics Core (BIC) of the Molecular Transducers of Physical Activity Consortium (MoTrPAC) tasked with building a molecular map of physical activity (MoTrPAC - https://commonfund.nih.gov/moleculartransducers/overview). The Bioinformatics Core is supervised by co-PIs Dr. Euan Ashley and Dr. Matthew Wheeler in the Division of Cardiovascular Medicine at Stanford University. Dr. Ashley’s research focuses on leveraging emerging technologies such as genomics and wearable sensors to provide insights into precision medicine (https://ashleylab.stanford.edu/). Dr. Wheeler’s research focuses on genomics, rare myocardial and skeletal muscle disease, and undiagnosed diseases (https://undiagnosed.stanford.edu). Group members have opportunities for cross-disciplinary collaboration and engagement with clinical, translational, wet lab, and dry lab researchers.
The BIC’s goal is to study the molecular changes that occur during and after exercise to advance the understanding of how physical activity improves and preserves health. This incredible project integrates very large volumes of clinical and densely time sampled molecular data (genomic, epigenomic, transcriptomic, proteomic and metabolomic data). The bioinformatics core is building cutting edge infrastructure to manage, analyze and disseminate this resource to the research community through the Google Cloud Platform. Our portal (https://motrpac-data.org/) will push the boundaries of biomedical data analytics to provide insight into basic and translational science of exercise.
The role of Bioinformatics Engineer will focus on the development of pipelines and tools for the comprehensive analysis of large amounts of molecular and clinical data being generated by the consortium, with special emphasis on Metabolomics and Proteomics datasets. Your ability to participate in software development projects, understand MS-based molecular data and experimental design will be a key resource in enabling high-quality data to flow through our systems to enable analytical insights.
- Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness.
- Determine additional data collection and reporting requirements.
- Design and customize reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data.
- Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others.
- Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
- Serve as a resource for non-routine inquiries such as requests for statistics or surveys.
- Test prototype software and participate in approval and release process for new software.
- Provide documentation based on audit and reporting criteria to investigators and research staff.
- Design and develop software applications that may involve sophisticated data manipulation.
* Other duties may also be assigned
- Graduate degrees that emphasize engineering, computer science, and statistics are preferred
- Experience with mass spectrometry-based data analysis
- Proficiency in Python and Linux bash scripting
- Demonstrated adherence to best practices in software engineering, including usability, testing, and source code version control (e.g. git)
- Experience with cloud computing environment
- Exposure to container systems such as setting up virtual machines and Docker instances
- Experience on a bioinformatics and/or software development team-based project
- Familiarity with build/release/deploy and continuous integration frameworks
- Familiarity with the R programming language
- Biological domain knowledge
- Experience in exercise science and/or untargeted metabolomics-based / proteomics projects
- An understanding of data modeling including ontologies and database design
EDUCATION & EXPERIENCE (REQUIRED):
- Bachelor's degree and three years of relevant experience or combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
- Substantial experience with MS Office and analytical programs.
- Excellent writing and analytical skills.
- Ability to prioritize workload.
CERTIFICATIONS & LICENSES:
- Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.
- Occasionally use a telephone.
- Rarely writing by hand.
*- Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
Some work may be performed in a laboratory or field setting.
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University’s Administrative Guide, http://adminguide.stanford.edu/.
- Schedule: Full-time
- Job Code: 4752
- Employee Status: Regular
- Grade: I
- Requisition ID: 85663