Stanford Blood Center
Research Data Analyst 2
Stanford Blood Center, Palo Alto, California, United States, 94306
Stanford University is seeking a Bioinformatics Engineer to manage and analyze large amounts of information, typically technical or scientific in nature, independently with minimal supervision.
About the Department of Pathology:
Comprised of extraordinary faculty and staff, our mission is to improve the ability to diagnose, treat and understand the origin and manifestation of human disease, and to care for those who have or are at risk to develop disease. We accomplish this through our clinical services and research, and also by educating future leaders in pathology and related fields.
For more information about the department visit
http://pathology.stanford.edu/ About GREGoR Stanford Site: GREGoR Stanford Site (GSS) is one of 6 sites in the National Institutes of Health (NIH)’s Genomics Research to Elucidate the Genetics of Rare disease (GREGoR) Consortium. The GSS ( https://gregor.stanford.edu/ ) mission is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease through integrated analysis of multi-omics data. About the Position: We are seeking a highly talented and motivated Bioinformatics Engineer to support our GSS pipeline and data analysis team. Your role will focus on the development of pipelines and tools for comprehensive analysis of large amounts of molecular data generated by the GSS, with special emphasis on genomics, transcriptomics, and metabolomics datasets. You will also establish and support cloud infrastructure for storage and computation of the multi-omics data. Duties Include: Development of pipelines and tools for the comprehensive analysis of large amounts of multi-omics data being generated by the GSS. Establish and maintain the cloud infrastructure for GSS on AnVIL and GCP. Interact with GREGoR team members as well as external tool developers to implement new tools, algorithms, and updates. Develop intuitive reports for molecular pipelines for tracking progress and quality metrics. Track reports for problems with pipeline analysis and underlying data. Extract relevant data from a variety of sources, including RESTful API services, databases and medical records. Serve as a resource for bioinformatics inquiries from the clinical team members to access data or results from local cluster/cloud/external provider. Work with stakeholders across the consortium to best understand data structures to model metadata schemas. Mentorship to Junior Analysts with regards to primary analysis. Document and report as needed to fulfill grant and regulatory obligations. Desired Qualifications: Graduate degree (Ph.D or M.S) that emphasizes bio/medical informatics, engineering, computer science and statistics are preferred. Relevant work experience preferred, two or more years. Domain expertise in analysis and running pipelines and bioinformatic tools for at least one of the following ‘omes': genomics, transcriptomics, metabolomics. Proficiency in Python and/or R and Linux bash scripting. Experience with pipeline languages like WDL or snakemake or nextflow. Proven track record of data and infrastructure management in a HPC (High Performance Computing) cluster or cloud computing like Google Cloud Platform or AWS. Experience with container systems such as setting up virtual machines and docker instances. Experience and knowledge of code management such as GitHub. Experience in systems biology approaches for data integration is a plus. Experience in developing tools and statistical methods for large-scale data analysis is a plus. Biological domain knowledge (rare disease) is a plus. Experience on bioinformatics and/or software development team-based projects. Willingness to work in a highly collaborative environment. Strong communication skills (e.g., put together reports and presentations). Ability to work independently. Education & Experience (Required): Bachelor's degree and three years of relevant experience or combination of education and relevant experience. Knowledge, Skills, and Abilities (Required): Substantial experience with MS Office and analytical programs. Excellent 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. The expected pay range for this position is $104,358 to $128,038 per annum. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
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http://pathology.stanford.edu/ About GREGoR Stanford Site: GREGoR Stanford Site (GSS) is one of 6 sites in the National Institutes of Health (NIH)’s Genomics Research to Elucidate the Genetics of Rare disease (GREGoR) Consortium. The GSS ( https://gregor.stanford.edu/ ) mission is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease through integrated analysis of multi-omics data. About the Position: We are seeking a highly talented and motivated Bioinformatics Engineer to support our GSS pipeline and data analysis team. Your role will focus on the development of pipelines and tools for comprehensive analysis of large amounts of molecular data generated by the GSS, with special emphasis on genomics, transcriptomics, and metabolomics datasets. You will also establish and support cloud infrastructure for storage and computation of the multi-omics data. Duties Include: Development of pipelines and tools for the comprehensive analysis of large amounts of multi-omics data being generated by the GSS. Establish and maintain the cloud infrastructure for GSS on AnVIL and GCP. Interact with GREGoR team members as well as external tool developers to implement new tools, algorithms, and updates. Develop intuitive reports for molecular pipelines for tracking progress and quality metrics. Track reports for problems with pipeline analysis and underlying data. Extract relevant data from a variety of sources, including RESTful API services, databases and medical records. Serve as a resource for bioinformatics inquiries from the clinical team members to access data or results from local cluster/cloud/external provider. Work with stakeholders across the consortium to best understand data structures to model metadata schemas. Mentorship to Junior Analysts with regards to primary analysis. Document and report as needed to fulfill grant and regulatory obligations. Desired Qualifications: Graduate degree (Ph.D or M.S) that emphasizes bio/medical informatics, engineering, computer science and statistics are preferred. Relevant work experience preferred, two or more years. Domain expertise in analysis and running pipelines and bioinformatic tools for at least one of the following ‘omes': genomics, transcriptomics, metabolomics. Proficiency in Python and/or R and Linux bash scripting. Experience with pipeline languages like WDL or snakemake or nextflow. Proven track record of data and infrastructure management in a HPC (High Performance Computing) cluster or cloud computing like Google Cloud Platform or AWS. Experience with container systems such as setting up virtual machines and docker instances. Experience and knowledge of code management such as GitHub. Experience in systems biology approaches for data integration is a plus. Experience in developing tools and statistical methods for large-scale data analysis is a plus. Biological domain knowledge (rare disease) is a plus. Experience on bioinformatics and/or software development team-based projects. Willingness to work in a highly collaborative environment. Strong communication skills (e.g., put together reports and presentations). Ability to work independently. Education & Experience (Required): Bachelor's degree and three years of relevant experience or combination of education and relevant experience. Knowledge, Skills, and Abilities (Required): Substantial experience with MS Office and analytical programs. Excellent 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. The expected pay range for this position is $104,358 to $128,038 per annum. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
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