Associate Principal Scientist: Drug Discovery - Computational Biologist Multi-Omics

Bayer•Cambridge, MA

3d•$124,960 - $187,440•Onsite

About The Position

We are looking for a highly creative and motivated Computational Biologist for Multi-omics analysis to join Bayer's Chemical Biology, Imaging and Omics (CBIO) sub-cluster within Drug Discovery Sciences in the Bayer Research and Innovation Center (BRIC) in Cambridge (MA). At CBIO, you will be part of an interdisciplinary team of scientists within the R&D organization, supporting projects across the R&D portfolio and contributing to excellence in early drug discovery. You will leverage your expertise in Computational Biology and state-of-the-art data analysis skills to design and interpret Multi-omics experiments, addressing drug discovery challenges from target identification to drug development.

Requirements

Ph.D. in Computational Biology, Systems Biology, Chemical Biology, Biology, or related Life Sciences with demonstrated expertise in Computational Biology and strong understanding of Biology and Experimental Biology
Extensive hands-on experience in multi-omics data analysis (Transcriptomics, Proteomics, ATAC-seq, Ribo-seq, etc.). Application of these methods to the study of compound biology / chemical biology is a plus
Demonstrated success in designing and interpreting complex biological experiments, particularly in Chem-Omics
Proven ability to extract meaningful biological insights from quantitative datasets through deep understanding of chemical biology, cell biology, and disease biology
Track record of successfully integrating multiple omics datasets to generate novel insights
Strong understanding of experimental workflows and ability to collaborate with wet-lab colleagues for optimization and troubleshooting
Expert knowledge of programming languages (Python or R) and statistical methods relevant to Computational Biology
Outstanding interpersonal and communication skills with demonstrated ability to work effectively in cross-disciplinary teams

Nice To Haves

4+ years of postdoctoral experience or relevant industry experience
Experience in Chemo-informatics or Chemo-genomics is highly desirable
Knowledge of spatial omics analysis is advantageous

Responsibilities

Drive pivotal scientific questions in drug discovery projects as a purpose-driven drug hunter, providing critical insights for go/no-go decisions and advancing our understanding of targets and modalities
Design and execute integration of multi-omics data (Chemo-proteomics, Transcriptomics), analyzing single or multiple omics layers to generate novel insights into disease, target, and compound biology
Develop and implement cutting-edge computational tools and pipelines for complex multi-omics data analysis
Actively participate in drug discovery project teams, contributing to target identification and validation, modality discovery, and mode-of-action deconvolution
Transform multi-parametric data into testable hypotheses through iterative collaboration with wet lab scientists and data scientists
Champion AI-enabled drug discovery and actively contribute to AI-driven projects
Scout and evaluate innovative approaches through partnerships with CROs, biotech, and academia
Contribute to scientific publications and present at conferences to enhance our research visibility and demonstrate scientific excellence