We are seeking a bioinformatics scholar with strong interests in high-dimensional flow and mass cytometry, omics technologies, and systems immunology, as well as deep expertise in the development and application of bioinformatics methods and tools to emerging challenges in immunology research. Together, we hope to foster creative thinking that will move the field closer to treatments of immune mediated diseases.
- Perform cytometry data annotation, curation, and harmonization as needed.
- Work independently and collaboratively with Long lab and HIP Core researchers to design, implement, and analyze new immunological experiments.
- Evaluate emerging computational methods and tools for cytometry data processing and analysis. Recommend, adapt, and implement best-of-class data processing/analysis pipelines for large-scale application at BRI.
- Develop, adapt, extend, and implement best-of-class methods (i) to integrate cytometry data from multiple batches and projects, (ii) to integrate cytometry data from different platforms, (iii) integrate cytometry data with other data sets such as bulk/single-cell RNA-seq, ATAC-seq, and proteomics.
- Educate HIP Core and Long lab scientists in bioinformatics, biostatistics, and computational best practices.
- Attend and present data at external scientific meetings and conferences as appropriate.
- Facilitate best visualization of data as appropriate and publish papers
- Set and meet deadlines and milestones.
- Be forward thinking by welcoming opportunities for additional training and engagement with the larger scientific community
- Foster a friendly, collaborative learning environment that prioritizes integrity and respect, innovation and agility, and constant inquiry.
- Ph.D. in bioinformatics, biostatistics, computational biology, systems biology/immunology; or in other STEM disciplines with a strong understanding of the principals of bioinformatics and high-throughput technologies; alternatively an M.S. in the above listed fields and 3 or more years professional experience.
- Demonstrated track record of technical proficiency, scientific creativity, collaboration with others, and independent thought.
- Excellent oral and written communication skills.
- Excellent time management, task organization, and multi-tasking skills.
- Good understanding of molecular biology, genetics, and immunology.
- Deep understanding of ‘Big Data’ and high-dimensional-data analysis methods (e.g. feature-selection, dimensionality reduction, pattern recognition, machine learning).
- Proficiency operating in a mixed UNIX-Mac-Windows environment.
- Programming skills in Unix shell scripting languages (sh/sed/awk).
- Proficiency in bioinformatics analysis using R/Bioconductor and Python.
- Familiarity with version management, high-performance and cloud computing environments, job scheduling, batch-processing, and workflow management systems.
Benaroya 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.
We strongly support and encourage applicants from diverse backgrounds including race, color, religion, sexual orientation, gender identity, national origin, citizenship, disability or protected veteran status.