R Developer / Bioinformatic
Posted
start date: 18/01/2027
About the project: The project is creating web applications for the statistical analysis of preclinical studies. As part of the analysis, longitudinal data are modeled, then visualized and reported. The project involves the development and maintenance of several R and Python libraries, including integration with the study data acquisition system, user-generated data manipulation, and customization of visualizations. A separate module is used to conduct meta-analyses based on multiple studies. The analysis results are then shared with an external service via asynchronous API endpoints.
Techstack:
- R (shiny, R6, ggplot2, tidyverse, testthat)
- Python (FastAPI, pydantic, async, Motor)
- MongoDB z GridFS
- API (REST oraz GraphQL)
- Docker
- Github Actions
1. Minimum 2 years of experience in coding in R
2. Experience in developing R packages
3. Good knowledge of Shiny
4. Good knowledge of plotly, ggplot packages
5. Good knowledge of using version system control (Git)
6. Good knowledge of bash command line and Unix environment
7. Knowledge of using Docker is a plus
8. Knowledge of HTML, JavaScript, jQuery and CSS is a plus
9. Knowledge of mongoDB, SQL is a plus
10. Knowledge of unit testing is a plus
11. English at least at B2 level
12. Good understanding of biological concepts and experimental methods commonly used in molecular biology and interest to learn more
13. Experience with Bioconductor libraries
14. Experience with sequencing/genomic data analysis (NGS, e.g. RNA-Seq, WGS, scRNA-Seq) and familiarity with bioinformatics tools used to process such data is a plus
Bioinformatic Senior:
1. Minimum 4 years of experience in coding in R
2. Experience in developing R packages
3. Very good knowledge of Shiny
4. Very good knowledge of plotly, ggplot packages
5. Good knowledge of using version system control (Git)
6. Good knowledge of bash command line and Unix environment
7. Knowledge of using Docker
8. Knowledge of HTML, JavaScript, jQuery and CSS
9. Knowledge of mongoDB, SQL is a plus
10. Knowledge of unit testing is a plus
11. English at least at B2 level
12. Good understanding of biological concepts and experimental methods commonly used in molecular biology and interest to learn more
13. Experience with Bioconductor libraries
14. Experience with sequencing/genomic data analysis (NGS, e.g. RNA-Seq, WGS, scRNA-Seq) and familiarity with bioinformatics tools used to process such data
15. Good knowledge of unit testing and front-end testing (i.e. R/Selenium, phantomjs)