At Sage Bionetworks, we are working to establish actionable biomedical observations through the reliable analysis and responsible sharing of biomedical data. We believe that by improving the way scientists collaborate and by increasing the reliability of research, we will improve human health.
Sage Bionetworks is currently recruiting for computational biologists or data scientists with a background in biomedical research. This position will support data and research coordination within consortia focused on human disease. Ideal candidates will have a strong background in statistical modeling, machine learning, and data analysis, particularly as applied to large-scale, high-dimensional data sets. In particular, we are interested in candidates who have experience with multiple data modalities including omics and biomedical imaging to support the development of systems for validating, harmonizing, visualizing, annotating, and analyzing biomedical data. The work is inherently collaborative; the position will work closely with scientists and engineers inside Sage and with external researchers.
What you’ll be doing:
- Provide scientific leadership in the goals, architecture, and implementation of data and research coordination in large consortia.
- Work with bioinformatics engineers to identify or develop pipelines for data processing, including sequencing, imaging, and clinical data. Develop data QC routines for standardized data.
- Work with data curators to identify and/or define appropriate data models and schemas for expected data types and for new data types.
- Contribute to conceptualization and support of expert working groups in various domains, e.g. single cell processing & analysis. Advise and support analysis on contributed datasets. Contribute to manuscripts resulting from standards development or scientific results.
- Lead and contribute to grants and manuscripts.
- Mentor Sage research scientists and interns.
We’d love to hear from you if you have:
- A Ph.D. in computational biology, bioinformatics, biomedical engineering or related quantitative discipline and 2+ years of postdoc or post-graduate experience.
- Experience working with omics data, including bulk, single cell, and spatial molecular data.
- Experience working with high-dimensional molecular imaging data such as CyCIF, multiplex-IF, multiplex-IHC, Codex, MIBI, etc.
- Experience with scientific computing in cloud or HPC environments.
- Programming skills in Python or R.
In light of recent concerns of Covid-19, all interviews will be conducted remotely, and most positions will be remote through at least June 30, 2021. The option to work on-site at our Seattle office prior to June 30, will be considered upon request.