Principal Scientist, Computational Designer (Biologics & Peptides)

Bayer•Boston, MA

27d•$139,840 - $209,760•Onsite

About The Position

We are seeking a Computational Designer to advance our biologics and peptide discovery programs through data-driven molecular design at our Bayer Innovation Campus at the heart of Kendall Square in Cambridge, MA. In this role, you will partner closely with protein engineers, peptide chemists, structural biologists, assay teams, and key discovery partners in antibody or peptide generation and engineering to translate hypotheses into designed sequences and prioritize candidates for experimental testing. You will contribute to rapid design–make–test–analyze (DMTA) cycles, helping teams make structured, data-driven decisions and accelerating progression from lead concepts toward high-quality discovery candidates.

Requirements

PhD in Computational Biology, Biophysics, Bioinformatics, Chemical/Biological Engineering, Structural Biology, or related discipline.
Proven scientific and project leadership capabilities in cross‑functional research environments
Expertise in protein and peptide structure modeling, antibody design, molecular dynamics, free-energy and physics-based scoring, and machine-learning-guided design, including proficiency with state-of-the-art AI tools for co-folding, structure prediction, and de novo binder generation
Ability to work with and interpret large experimental data sets (binding/functional assays, biophysical characterization, developability screens).
Excellent problem-solving skills and the ability to work independently and collaboratively in a cross-functional environment.
Excellent communication and negotiation skills, pronounced intercultural competence and strong team orientation
Enjoy working in self‑organized teams, taking ownership and accountability for the full value chain

Nice To Haves

5+ years professional experience (industry or equivalent) in peptide and therapeutic antibody drug discovery with deep knowledge of the scientific literature and industry practices
Experience working with large-scale compute environments (HPC, cloud), containers, and workflow orchestration
Understanding of developability considerations for biologics (immunogenicity risk, viscosity, stability, liabilities) and relevant in silico assessments
Familiarity with antibody or peptide conjugate modalities (e.g., antibody–drug conjugates, oligonucleotide, radionuclide or peptide payloads)

Responsibilities

Initiate, drive and support drug discovery projects as an active member and leader of highly interdisciplinary, cross‑organizational teams
Apply structural and biological knowledge to connect targets with suitable modalities. Define tailored lead-finding strategies by characterizing protein-protein and protein-ligand interactions, identifying druggable pockets and epitopes, and designing biomolecules.
Design and optimize antibodies and peptides using structure-based and sequence-based computational and AI approaches, in partnership with antibody engineering teams and machine learning solution providers.
Build and apply modeling pipelines for affinity, specificity, stability, developability, and manufacturability-related properties (e.g., aggregation/solubility risk, PTM liabilities).
Generate and triage design hypotheses by integrating structural data (X-ray/cryo-EM), sequence/omics data, biophysical/assay results, and literature.
Develop automated workflows for candidate generation, scoring, and selection and data integration across programs.
Collaborate with wet-lab teams to define design goals, interpret experimental data, iterate designs and identify opportunities for acceleration with AI capabilities.
Partner with IT/HPC stakeholders to ensure appropriate compute infrastructure, software environments, and access patterns to deliver reliable modeling workflows and analytics.
Be a driver of innovation and take ownership with your peers to further develop and innovate antibody, peptide and conjugate lead discovery and optimization.
Communicate results to cross-functional stakeholders through concise reports, visualizations, and presentations.