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 Bioinformatics Engineers/Analyst with strong quantitative experience in biomedical research. Key tasks will involve supporting biomedical collaborations via analysis of multimodal and clinical datasets (e.g., ). Our research areas include immuno-oncology, precision medicine, spatial-temporal tumor heterogeneity, physical characterizations of tumor cells, and immune phenotyping. This position will facilitate benchmarking efforts related to assessing biomedical methods and tools and will assist establishing standards and benchmarks for biomedical and bioinformatic communities.
What you’ll do:
- Assess data quality across multiple data modalities, including genomic variant data, gene expression data, clinical and demographic data, and image data as well as other data types to be used in crowdsourced model building efforts and other open science projects.
- Conduct feasibility analysis, signal validation, power analysis and data harmonization..
- Conduct analyses and meta-analyses across multiple translational datasets utilizing regression modeling, survival analysis and as well as machine learning approaches.
- Implement baseline and published models to facilitate methods benchmarking.
- Collaborate with in-house data curation experts to select and apply data standards to consortia datasets.
- Visualization and writing skills.
- Cloud computing, data science bucket
We’d love to hear from you if:
- You’re enthusiastic about open science, collaboration, benchmarking and reproducible research.
- You have a masters degree in statistics, mathematics, bioinformatics, physics, computational biology, epidemiology, or related quantitative discipline, OR a bachelor’s degree in one of the above areas with 3+ years of relevant work experience
- You have experience working with high-dimensional biological data, such as gene expression, genomic, imaging, drug response, flow cytometry, or CyTOF.
- You have experience addressing a defined problem or hypothesis (biological or otherwise) creatively and with minimal supervision.
- You are competent in R and/or Python.
- You are passionate about reproducible data
- You have strong collaboration, teamwork and communication skills.
- Software development skills, including experience with version control software (e.g., Git).
- Experience with cloud computing (especially AWS) and containerization approaches (principally Docker). Extensive understanding of machine learning methods.
In light of recent concerns of Covid-19, all interviews will be conducted remotely, and most positions will be remote through at least December 31, 2020. The option to work on-site at our Seattle office prior to December 31, will be considered upon request.