Computational Biologist - Spatial Multi-Omics

Computational Biologist – Spatial Multi‑Omics

Join our Translational Sciences Cardiovascular Renal Team at the Bayer Innovation Campus in Kendall Square, Cambridge, MA.

• Build and maintain scalable pipelines for spatial and deep visual multi‑omics analysis, including data ingestion, QC, normalization, batch correction, feature extraction, and annotation from mass‑spectrometry and transcriptomics platforms.
• Integrate spatial metabolomics/proteomics with transcriptomics, genomics, and histopathology images to deliver multi‑modal insights for target discovery, biomarker development, and mechanism‑of‑action studies.
• Evaluate, benchmark, and optimize tools and workflows; contribute to internal software (R/Python) and visualization frameworks to streamline spatial omics analytics.
• Perform spatially aware statistical analyses to identify regulated molecular markers across tissue regions, cell types, and phenotypes.
• Develop and apply algorithms for spatial segmentation, clustering, co‑localization, neighborhood analysis, and spatial correlation; conduct pathway/network analyses.
• Collaborate with experimental biologists, pathologists, chemists, and clinicians to shape hypotheses, design studies, and translate findings into decisions for research programs.
• Document pipelines and analyses to ensure reproducibility, compliance, and knowledge transfer; prepare clear visualizations and narratives for internal reviews, publications, and external collaborations.
• Partner with data engineering/IT to manage large spatial datasets, define metadata standards, and implement versioning, governance, and access control best practices.

• 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, including QC, normalization, feature extraction, and statistical interpretation.
• Background in image analysis and spatial statistics (segmentation, registration, spatial point patterns, neighborhood analysis); exposure to machine learning or deep learning for omics or imaging data.
• Familiarity with MS and spatial tools like MZmine, Max Quant, Proteome Discoverer, Skyline, OpenMS, etc.; and spatial frameworks like Squidpy, Giotto, Seurat/Spatial, Napari, ImageJ/Fiji, Cell Profiler, etc.
• Experience with pathway/network analysis (e.g., KEGG, Reactome, Metabo Analyst, Cytoscape).
• 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 to interpret results and design analyses.
• Strong communication skills; experience collaborating within interdisciplinary teams and presenting complex results to diverse audiences.

Employees can expect to be paid a salary between $ - $. Additional compensation may include a bonus or commission (if relevant). Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc.

United States:
Massachusetts:
Cambridge

Bayer is an Equal Opportunity Employer/Disabled/Veterans. Bayer is an E‑Verify Employer. Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities.