Sage Bionetworks, Seattle, WA
At Sage Bionetworks, we believe that we can learn more by learning from each other. By improving the way scientists collaborate, we help to make science more effective. We partner with researchers, patients, and healthcare innovators to drive collaborative data-driven science to improve health. Making science more open, collaborative, and inclusive ultimately advances biomedicine.
We are currently recruiting a computational biologist with a background in analysis of translational study data, including genomics, transcriptomics, pathology, radiology and clinical/phenotype data. Experience with epidemiology and population studies is also of interest. We are active in a number of research areas including immuno-oncology, precision medicine, spatial-temporal tumor heterogeneity, physical characterizations of tumor cells, and immune phenotyping. The research scientist will contribute to data sharing consortia, including AACR’s Project GENIE and others organized by federal, non-profit, and industry sponsors. The scientist may contribute to organization and analysis of DREAM Challenges.
What you’ll be doing:
- Develop and execute quality assessment routines for translational study datasets contributed by external collaborators. Establish procedures for execution of quality routines in production.
- Conduct feasibility assessments, supporting studies in precision medicine and immunotherapy. Develop proposals for new studies using consortia/in-house and publicly available datasets.
- Design and conduct analyses and meta-analyses across multiple translational datasets.
- Summarize research findings in reports, manuscripts, and presentations to collaborators and funders.
- Develop new methods, pipelines, and tools as needed for analysis of data from funded projects, in collaboration with external partners. Generate preliminary data to support grant applications.
- Collaborate with in-house data curation experts to select and apply data standards to consortia datasets.
- Pilot methods to use cloud computing resources to analyze datasets held in Sage’s Synapse data sharing platform.
- Work with Sage’s software engineering team to define use cases and requirements for new features in Synapse.
We’d love to hear from you if you have:
- A PhD in computational biology, bioinformatics, statistics, epidemiology, mathematics, or related quantitative discipline, OR a masters degree in one of the above areas, 7+ years of relevant work experience, and a strong publication track record.
- Experience working with high-dimensional biological data, such as gene expression, genomic, imaging, drug response, flow cytometry, or CyTOF. Immediate needs and emphasis are in whole-exome sequencing, RNA-seq, and pathology imaging.
- Demonstrated ability to address a defined problem or hypothesis (biological or otherwise) creatively and with minimal supervision.
- Programming competence in R and/or Python.
- Collaboration, teamwork, presentation, and communication skills.
- Familiarity with cancer research.
- Software development skills, including experience with version control software (e.g., Git).
- Experience with cloud computing (especially AWS) and containerization approaches (principally Docker).
- Experience with performing meta-analyses.