The Department of Medicine, Division of Cardiovascular Medicine at Stanford University, is seeking a highly motivated Bioinformatics Engineer to join the Bioinformatics Core (BIC) of the Molecular Transducers of Physical Activity Consortium (MoTrPAC). MoTrPAC is part of the Common Fund Data Ecosystem (CFDE) and aims to build a comprehensive molecular map of physical activity. The BIC is responsible for managing, analyzing, and disseminating large volumes of molecular and clinical data generated by the consortium through the Google Cloud Platform. As a Bioinformatics Engineer, you will play a key role in developing pipelines and tools for the analysis and integration of multiomics datasets and enabling analytical insights.
The Common Fund Data Ecosystem (CFDE) is a collaborative effort by the National Institutes of Health (NIH) to establish a shared infrastructure that supports the efficient and effective management, analysis, and dissemination of biomedical research data. The CFDE aims to harmonize data management practices and facilitate data sharing across the scientific community, enabling researchers to work with large, complex datasets and extract new insights. As part of the MoTrPAC consortium, the Bioinformatics Core (BIC) is contributing to the CFDE by developing cutting-edge infrastructure to manage and analyze large volumes of molecular and clinical data generated by the consortium. The BIC's work will help advance the CFDE's mission of promoting data-driven research and accelerating scientific discoveries. As a Bioinformatics Engineer, you will have the opportunity to work within this ecosystem and contribute to the development of innovative solutions that facilitate data sharing and promote scientific collaboration.
This is an exciting opportunity to work in a data federation and be part of a cutting-edge project that integrates a variety of molecular data types, including genomic, epigenomic, transcriptomic, proteomic, and metabolomic data, to advance the understanding of how physical activity improves and preserves health. You will have opportunities for cross-disciplinary collaboration and engagement with clinical, translational, wet lab, and dry lab researchers.
To be successful in this role, you must have a strong background in bioinformatics and experience working with large-scale biological datasets. Proficiency in programming languages and exposure to high-performance computing environments is essential. You will be expected to participate in software development projects and have the ability to understand biological experiments. A complete application will include a cover letter highlighting your interest in the project and relevant qualifications.
Duties include:
Collect, manage and clean datasets.
Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in data.
Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.
Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.
Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.
Analyze data processes in documentation.
Collaborate with faculty and research staff on data collection and analysis methods.
Provide documentation based on audit and reporting criteria to investigators and research staff.
Communicate with government officials, grant agencies and industry representatives.
The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.
DESIRED QUALIFICATIONS:
Experience as a research assistant or similar.
Experience (including any graduate school) developing tools for data analysis.
Proficiency in python and/or R programming languages.
Experience with cloud computing environments.
Exposure to container systems such as setting up virtual machines and Docker instances.
Biological domain knowledge (exercise science is a plus).
Experience with omics projects.
An understanding of data modeling including ontologies and database design.
Strong data analysis skills to identify patterns, relationships, and inconsistencies within metadata.
Experience in working with large-scale data repositories and data management systems.
EDUCATION & EXPERIENCE (REQUIRED):
Bachelor's degree or a 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.
Strong writing and analytical skills.
Ability to prioritize workload.
PHYSICAL REQUIREMENTS:
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.
WORKING CONDITIONS:
Some work may be performed in a laboratory or field setting.
WORKING STANDARDS:
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/.
The expected pay range for this position is $64,480 to $93,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
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