Seeking scientists who are passionate about developing algorithms and deploying tools for the analysis of -omic data to join our disease cancelling technology team.
Immuneering’s Disease Cancelling Technology (DCT) computational platform accelerates target identification and drug discovery. We are expanding DCT by creating tools and interactive interfaces to facilitate interpretation of the insights generated by our algorithms.
We are looking for a computational biologist with a strong background in tool development. The ideal candidate has experience with R package and shiny development, has created and managed databases, and is an expert at applying statistical analysis and machine learning to genomic datasets.
Our team consists of brilliant people willing to share their knowledge and eager to learn from each other. You will work in a collaborative and nurturing environment that values diversity, personal development and integrity. We believe that diverse perspectives and experiences drive innovation. Immuneering is a Great Place to Work-Certified company with an excellent work-life balance.
San Diego, New York or Cambridge
- Create bioinformatic tools using custom R packages
- Create and deploy interactive shiny apps for visualization of results from our Disease Cancelling Technology
- Collaborate with colleagues to develop analysis methods and algorithms to solve complex computational research problems
- Leverage SQL or other databases for data storage
- Present scientific material (written and oral) to diverse audiences
- PhD in Bioinformatics, Computational Biology, Biostatistics or a related field (i.e., Biology, Engineering, Computer Science, Mathematics, Statistics) or 5+ years of work experience at a leading computational biology focused institution
- Proficient in R, comfortable writing functions and unit tests
- Experience processing gene expression/RNA-seq
- Proficiency writing packages to run analysis of large data sets (ideally transcriptomic, genomic, proteomic, and/or epigenomic data)
- Experience applying machine learning approaches to analysis of -omic data in pre-clinical settings
- Experience developing effective visualization tools using ggplot2, plotly, d3
- Background developing and deploying shiny apps
- Proven ability to work independently as well as contribute to large projects
- Knowledge of version control with git
- Knowledge of clean code and test-driven development
- Willingness to learn
- Effective English communication skills (both written and oral)
Preferred Additional Qualifications
- Broad and deep understanding of genetics, proteomics, and/or genomics as documented by a strong publication record in high-impact journals
- Experience processing and interpreting single cell RNA-seq datasets
- Experience studying human disease using genomic approaches, especially leveraging transcriptomic data
- Understanding of tidyverse packages
- Experience creating and managing docker images
- Python scripting, especially numpy, pandas, scikit learn, tensorflow or keras
- Strong scientific communication; excellent writing and presentation skills
To apply, contact email@example.com ATTN: DCT Hiring Manager