The University of Chicago's Department of Statistics is seeking a Junior Research Assistant to analyze large-scale biological data sets and contribute to the development of open-source R and Python software for methodological research in plant microbiology and microbial ecology.
Requirements
- Proficient in R and Python for data analysis.
- Experience with biological or ecological data (e.g., RNA-seq, microbiome, metabolomics).
- Prior contribution to an open-source project or package.
- Familiarity with high-performance or cloud computing (Slurm, AWS, GCP).
- Background in high-dimensional or spatial statistics.
- Familiarity with tidyverse, Bioconductor, scikit-learn, and pandas.
- Comfort with Git and Linux command line.
Responsibilities
- Clean, annotate, and batch-correct high-throughput sequencing and phenotyping data.
- Design and execute pipelines for mutant detection and pathway analysis (e.g., PCA, sparse CCA, eCCA).
- Perform rigorous QC and visualization to validate findings.
- Develop and maintain R and Python packages that implement lab methods; write unit tests and documentation.
- Automate data workflows using Git, CI, and reproducible-research best practices.
- Summarize results in figures, slide decks, and draft sections of manuscripts.
- Provide technical support for ongoing projects (hardware, software, data transfer).
Other
- Master’s degree in Statistics, Computer Science, Bioinformatics, Computational Biology, or a closely related field by start date.
- Coursework or project experience in multivariate statistics and/or machine learning.
- Strong quantitative reasoning and problem-solving ability.
- Excellent written and oral communication skills.
- Ability to manage multiple tasks and meet deadlines in a collaborative setting.
