BiomeSense is working on developing the first ever at-home sample collection instrument to enable daily tracking of gut microbiomes, and an AI platform to leverage these novel datasets for biomarker discovery. The candidate will: (1) develop bioinformatic methods for community analysis of multi’omic datasets, (2) analyze multi’omic datasets, and (3) participate in the design and development of a platform for data storage and analysis. This role will directly support a 2-year NSF SBIR Phase II project.
Responsibilities
- Develop and validate a computational metatranscriptomics pipeline for human fecal samples.
- Extend the capabilities of our data analysis infrastructure to support multi’omic datasets.
- Support the analysis and interpretation of experiments intended to validate microbial RNA extraction and storage protocols.
- Coordinate with a cross-functional team of engineers to ensure that validated protocols are automatable and compatible with BiomeSense sample collection technology.
Preferred Skills and Competencies:
- Experience with univariate and multivariate statistics for hypothesis testing.
- Experience developing machine learning pipelines with ‘omic data.
- Experience with workflow management (Snakemake/NextFlow/Other)
- Experience with Bash, Python, and R.
- Experience analyzing biological time-series datasets.
- Familiarity with frontend web development (JavaScript and HTML)
- Familiarity with QIIME/QIIME2 and Qiita.
- Familiarity with best practices for software engineering (version control, reproducibility, unit testing, continuous integration, etc.).
- Familiarity with Amazon Web Services is a plus.