Apply here: https://careersearch.stanford.edu/jobs/bioinformatics-engineer-20912?et=1mP3OB5kD
About the Department of Pathology
Comprised of extraordinary faculty and staff, our mission is to improve the diagnosis, treatment and basic understanding of human disease. We accomplish this through our clinical services, research, and training the future leaders in pathology and related fields. A major focus of clinical research in the Department continues to be the correlation of patient outcome and treatment response with the surgical pathologic diagnosis of human cancers. Everything we do is to provide the highest quality of pathology diagnostic services to the patients for whom we passionately care.
For more information about the department visit http://pathology.stanford.edu/
As an organization that receives federal funding, Stanford University has a COVID-19 vaccination requirement that will apply to all university employees, including those working remotely in the United States and applicable subcontractors. To learn more about COVID policies and guidelines for Stanford University Staff, please visit https://cardinalatwork.stanford.edu/working-stanford/covid-19/interim-policies/covid-19-surveillance-testing-policy.
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. GSS is led by co-PIs Dr. Stephen Montgomery (Department of Pathology), Dr. Matthew Wheeler (Division of Cardiovascular Medicine) and Dr. Jon Bernstein (Division of Medical Genetics).
At GSS, research participants who remain undiagnosed after exome sequencing will undergo short read and long read genome sequencing, transcriptome sequencing, methylation assays, metabolomics and/or lipidomics assays. State-of-the art computational algorithms and new methods will be applied and developed to prioritize the variants and genes. The data will be analyzed in a secure and scalable manner using a HIPAA compliant cloud platform like AnVIL and Google Cloud Platform (GCP). Novel causal variants and genes will be validated through state-of-the-art targeted approaches including massively parallel reporter assays, induced-pluripotent stem cell assays and CRISPR engineered cellular and mouse models.
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. Your ability to understand biological experiments, strong experience in the analysis of large-scale biological datasets, proficiency with programming languages and experience in high-performance computing environments or cloud will be a key resource in enabling high-quality data to flow through our systems to enable diagnosis and discovery of new disease-gene associations.
A complete application will include CV and cover letter.
- 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.
- Communicate with government officials, grant agencies and industry representatives.
* - Other duties may also be assigned
- Bachelor’s degree in Mathematics, Statistics, Computer Science or related field.
- Research experience in computational biology desired; specifically in analysis of high-throughput, multiplexed and multi-omics data. Experience in designing data analysis pipelines is an advantage.
- Proficiency in Python and/or R and Linux bash scripting.
- The candidate should be able to work independently, be highly motivated, well organized, adaptable and work well within a highly interdisciplinary and international team. Good communication and interpersonal skills as well as fluent - English are essential, as well as proficient computer skills (Mac and PC).
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.