Overview In this Co Op, you will support analysis of single cell and spatial transcriptomics data to uncover biological insights. You'll collaborate with computational biologists, geneticists, and genomics scientists to explore datasets, evaluate new methods, and generate findings that inform discovery. You'll build reproducible analysis workflows and communicate results to cross functional teams. This role supports Bayer's mission to advance health and agricultural science in a multidisciplinary, research driven environment.
Compensation / Benefits- health care
- vision
- dental
- retirement
- PTO
- sick leave
Responsibilities- Analyze single cell and spatial transcriptomics datasets using modern computational approaches
- Explore datasets to identify novel biological insights and hypotheses
- Conduct literature reviews to identify emerging analytical methods
- Create reproducible analysis workflows and document methods
- Present findings, visualizations, and recommendations to multidisciplinary teams
Key requirements- Pursuing a Master's or Ph.D. degree in Bioinformatics, Computational Biology, Genetics, Genomics, Data Science, Computer Science, Statistics, or a related field
- Experience with biological data analysis using R and/or Python
- Familiarity with transcriptomics, single cell sequencing, or spatial biology data is preferred
- Knowledge of statistical modeling and data visualization techniques
- Strong problem solving, communication, and organizational skills
- Ability to work independently and collaboratively in a multidisciplinary research environment
- strong communication
- team collaboration
- organization
- R
- Python
- transcriptomics
