Role OverviewJoin Bayer's Translational Sciences Cardiovascular Renal Team as a Computational Biologist - Spatial Multi-Omics to develop and maintain scalable pipelines for spatial and deep visual multi-omics analysis. The role involves integrating various omics data types to drive insights for target discovery, biomarker development, and mechanism-of-action studies.
What You Will Do
Build and maintain scalable pipelines, integrate spatial metabolomics/proteomics with transcriptomics, genomics, and histopathology images, and perform spatially aware statistical analyses to identify regulated molecular markers.
Why It Might Be a Fit
The successful candidate will play a crucial role in driving insights for target discovery, biomarker development, and mechanism-of-action studies, and will have the opportunity to collaborate with experimental biologists, pathologists, chemists, and clinicians to shape hypotheses and design studies.
Requirements
- PhD in Computational Biology, Bioinformatics, Systems Biology, Biostatistics, Computer Science, or related field; or MSc with substantial relevant experience
- Hands-on experience analyzing mass spectrometry and transcriptomics spatial data
- Background in image analysis and spatial statistics
- Familiarity with MS and spatial tools like MZmine, MaxQuant, Proteome Discoverer, Skyline, OpenMS, etc.
- Experience with pathway/network analysis
- Proficiency in Python and/or R
- Comfort with Linux/Unix environments, high-performance computing, and version control (Git)
- Demonstrated ability in high-dimensional data analysis, statistics, and reproducible pipeline development
- Solid understanding of molecular biology, biochemistry, and metabolism
Benefits
- Health care
- Vision
- Dental
- Retirement
- PTO
- Sick leave
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