Computational Designer Jobs (NOW HIRING)

At Bayer we're visionaries, driven to solve the world's toughest challenges and striving for a world where 'Health for all Hunger for none' is no longer a dream, but a real possibility. We're doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining 'impossible'. There are so many reasons to join us. If you're hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there's only one choice.

Principal Scientist, Computational Designer (Biologics & Peptides) 

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.

 YOUR TASKS AND RESPONSBILITIES

The primary responsibilities of the Principal Scientist, Computational Designer are to:

• Initiate, drive and support drug discovery projects as an active member and leader of highly interdisciplinary, crossorganizational 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.

WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required qualifications:

 

• PhD in Computational Biology, Biophysics, Bioinformatics, Chemical/Biological Engineering, Structural Biology, or related discipline.
• Proven scientific and project leadership capabilities in crossfunctional 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 selforganized teams, taking ownership and accountability for the full value chain

Preferred qualifications:

• 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)

Employees can expect to be paid a salary between $139,840.00 - $209,760.00. Additional compensation may include a bonus or commission (if relevant).  Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc.

This salary range is merely an estimate and may vary based on an applicant's location, market data/ranges, an applicant's skills and prior relevant experience, certain degrees and certifications, and other relevant factors.

This posting will be available for application until at least 07/30/2026.

    YOUR APPLICATION      

Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer. 
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.
Bayer is an Equal Opportunity Employer/Disabled/Veterans
Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below. 

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