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This job expired on 31/08/2026. It no longer accepts applications.
R Developer with Life Science Background
Jobgether
Job description
About the role
This position is for an R Developer with a life‑science background, based in Spain. The role sits at the intersection of software engineering, data science, and biomedical research, creating production‑grade R and Shiny applications that support drug discovery, clinical trials and other biomedical analytics.
Key responsibilities
- Design, develop and maintain high‑quality R and Shiny applications for biological and clinical data analysis.
- Process, analyse and visualise complex life‑science datasets, ensuring reproducibility and usability.
- Build and maintain reusable R packages and data‑processing components for scalable analytics.
- Collaborate with scientists, bioinformaticians and stakeholders to translate requirements into technical solutions.
- Develop interactive visualisation tools to aid research and clinical decision‑making.
- Use Git for version control and collaborative development.
- Participate in system design discussions, backlog refinement and continuous improvement of development practices.
- Support deployment and maintenance of production‑grade applications in cloud or distributed environments.
Required profile
- Strong proficiency in R programming with hands‑on experience in production environments.
- Experience working with biological, clinical or life‑science data.
- Proven experience building web applications using R Shiny or JavaScript.
- Experience creating, maintaining and documenting R packages.
- Solid understanding of Git and collaborative software development workflows.
- Master’s degree in Bioinformatics, Data Science, Computer Science, Biostatistics, Mathematics or related field, or equivalent experience.
- Knowledge of molecular biology, genomics or clinical research is highly desirable.
Required skills
- R programming
- Shiny framework
- JavaScript (optional for web UI)
- Git version control
- Cloud or distributed computing environments
- Reproducible data pipelines
- Database interaction
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