At Bayer, the Machine Learning Research team is seeking a passionate research scientist to lead the development of innovative machine learning solutions for proteomic data analysis to accelerate the discovery of new medicines and address healthcare and sustainability needs.
Requirements
- Experience in omics data analysis, including development and evaluation of machine learning solutions to extract actionable insights from large, multiparametric omics datasets
- Excellent programming skills in Python
- Demonstrated expertise with data science, machine and deep learning libraries (e.g., PyTorch, JAX, scikit-learn), including relevant chemistry/biology libraries and software tools (e.g., RDkit, OEChem TK, Biopython)
- Experience with machine learning solutions for proteomic and/or chemo-proteomic data analysis
- Experience in drug discovery projects in target characterization, mode of action deconvolution, small-molecule hit generation, hit-to-lead, and/or lead optimization
- Familiarity with molecular modeling and design software (e.g., Maestro, LiveDesign, MOE, Discovery Studio, Flare, Pipeline Pilot)
- Strong record of publications or patents related to data science solutions for chemistry and/or biology
Responsibilities
- Identify opportunities to enhance R&D’s productivity and further our portfolio goals, across therapeutic areas, by leveraging proteomic and chemo-proteomic data with novel machine learning solutions
- Propose and catalyze the co-creation and implementation of interdisciplinary, machine learning solutions in support of target characterization, mode of action deconvolution, hit identification, and small-molecule design
- Collaborate with our experimental and computational R&D partners at Bayer and arm-lengths companies to prioritize, develop and ultimately leverage data science capabilities in support of our pipeline
- Work cross-functionally with data science, computational, and IT functions to deploy, scale-up, and operationalize relevant data science solutions
- Keep up to date with the latest advances in (chemo)proteomics data processing and analysis, and machine learning algorithms for protein-ligand structure and property prediction
- Contribute to the broader scientific community through publications, open-source projects, and conference presentations
- Apply an analytical, data-driven mindset to addressing business needs and goals
Other
- Ph.D. degree in Computational Chemistry/Biology, Chem/Bioinformatics, Chemical/Biological/Molecular Engineering, or a related field at the intersection of life sciences and computer science
- 8+ years of relevant post-PhD experience, including 4+ years in industry
- nurture the self-development of leadership traits (including acting as a mentor and coach, guiding teams toward business outcomes, facilitating company-wide connections and collaboration, and contributing to value creating systems that leverage the passion and energy of our people)
- Employees can expect to be paid a salary between $182,337.60 - $273,506.40.
- This posting will be available for application until at least 10/20/2025.
