Bioinformatics Postdoctoral Research Associate – Bioinformatics, Computational Biology, Machine Learning
- Benaroya Research Institute
- Location: Seattle, WA
- Job Number: 7087399 (Ref #: 1714)
- Posting Date: Oct 19, 2021
- Application Deadline: Open Until Filled
Job DescriptionBenaroya Research Institute at Virginia Mason (BRI) has a bold mission: Predict, prevent, reverse and cure immune system diseases, from autoimmune disease to cancer to COVID-19. We examine the immune system in both health and disease to understand how disorders start and how to rebalance the immune system back to health. Equipped with innovative tools and robust biorepositories, our team chips away at the biggest mysteries behind these conditions to work toward our vision of a healthy immune system for all. As an independent non-profit organization within Virginia Mason Franciscan Health, we collaborate with clinicians to accelerate the path from innovative lab discoveries to life-changing patient care.
At BRI, each role is valued and an important contributor to the vision and mission. BRI is committed to a safe, caring and diverse workplace; as well as to taking action to further our commitments to foster inclusion, equity and belonging so employees feel comfortable bringing their full selves to work. Consider making a difference, join our team. Because together, we are Powering Possibility.
Benaroya Research Institute (BRI) in Seattle, WA is seeking a bioinformatics and machine learning expert who has demonstrated experience working with large multi-omics, next-generation sequencing (bulk/single-cell) and single-cell cytometery datasets. Candidate should have working knowledge and skills in statistical analysis, regression analysis, graph theory, bayesian learning and other exploratory/inferential analytical tools. Individuals with background training in Dynamical Systems Analysis and/or Deep Learning are strongly encouraged to apply.
The individual will join as a Postdoctoral Research Associate in the Systems Immunology Group which is broadly engaged in basic and applied studies using complex systems theory, high throughput techniques as well as mathematical and computational tools to understand the functioning of the immune system in health and disease. The group works closely with informaticians and immunologists in many groups at BRI, resulting in a rich environment for quantitative, computational, and laboratory collaborations in immune disease research.
The candidate will implement bioinformatics analysis algorithms and develop analytical pipelines for extracting biomarkers from large time series datasets that will provide insights into mechanisms underlying successful response to treatment in clinical trials.
This position is remote, and is open to candidates anywhere within the U.S.A.
• Analyze multi-omics data to derive relevant insights using state-of-the-art statistical methods
• Implement pipelines and algorithms for different types of biological data analysis and visualization
• Perform integrative, pathway, and network analyses to understand disease mechanisms and discover insights
• Apply machine learning models for biomarker identification and patient stratification
• Effectively communicate analysis results via presentations
• Ph.D. (with 0-3 years of relevant experience) in Bioinformatics, Computational Biology, Machine Learning or related technical discipline
• Fluency with standard tools and data formats related to gene expression, RNA-seq, enrichment analysis, genetic, genomic, or cytometry data and perform high dimensional data mining, integration, and extraction
• Experience developing, training, and evaluating machine learning models for analysis of time series datasets; working know-how of dynamical systems analysis or deep learning methods is strongly preferred
• Fluency in Python and R or Matlab programming/scripting languages
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, disability or protected veteran status.