Senior Scientist, Antibody Engineering
About The Position
The Senior Scientist will lead and expand the SSF Antibody Engineering team's de novo protein and antibody design capability. The role applies AI/ML approaches to optimize the Design-Make-Test-Analysis (DMTA) cycle for discovery candidates and candidate nomination, and supports cross-functional projects. The successful candidate will connect computational and experimental sciences to help advance programs toward the clinic. The position involves contributing to program teams and understanding program biology to design antibodies, bispecific antibodies, T-cell engagers, antibody-drug conjugates, engineered cytokines, and other biologic therapeutics. The scientist uses computational and data-driven methods, including Python, AI/ML tools, bioinformatics, and in silico protein engineering, alongside experimental construct and assay design. The role also integrates experimental data into models and modality-specific engineering platforms, coordinates with CROs and external partners, contributes to data systems and scientific documentation, and maintains communication across relevant Astellas expert networks. The position is based in SSF and requires on-site work. Astellas also describes a hybrid working solution that may be permitted from certain locations under its Responsible Flexibility Guidelines.
Requirements
- PhD in Biochemistry, Biophysics, Computational Biology, Structural Biology, or a related field, with 5+ years of related industry and/or postdoctoral experience.
- Proficiency in Python programming or related scripting tools for biological data analysis, data visualization, workflow automation, and/or integration of computational and experimental datasets.
- Experience with generative AI for protein design, machine-learning model development, and structural biology tools such as PyMOL, Boltz, AlphaFold, or Rosetta.
- Familiarity with cloud computing, database management, and data engineering pipelines.
- Familiarity with different antibody formats and antibody-drug assessment and validation processes.
- Good practices in data management and recordkeeping.
- Strong work ethic and collaborative mindset, with flexibility, adaptability, and willingness to support critical team priorities beyond primary project responsibilities.
- Excellent written and verbal communication skills, including the ability to articulate computational and experimental strategies, present complex data, and communicate recommendations to diverse audiences.
Nice To Haves
- Hands-on experience in antibody or protein engineering and characterization.
- Knowledge of antibody discovery, affinity maturation, and developability assessment for biologics drug development.
- Experience with NGS-based protein engineering datasets.
Responsibilities
- Develop and expand the SSF Antibody Engineering Team's capability in AI/ML-based de novo protein and antibody design and engineering.
- Participate in program teams and understand program biology to support designs of antibodies, bispecific antibodies, T-cell engagers, antibody-drug conjugates, engineered cytokines, and other biologic therapeutics.
- Apply computational and data-driven approaches, including Python programming, AI/ML tools, bioinformatics, and in silico protein engineering, to therapeutic design, sequence analysis, data interpretation, and workflow automation.
- Design constructs and assays, including BLI, ELISA, cell-based binding and cytotoxicity assays, and developability assessments to support molecule selection and optimization.
- Integrate experimental data to improve AI/ML models and develop modality-specific AI/ML protein engineering platforms.
- Coordinate with CROs and external partners for protein production, analytical characterization, assay execution, and data review.
- Contribute to the biologics data management system, ELN, technical reports, documentation, invention disclosures, patent applications, and external presentations when appropriate.
- Maintain Astellas networks and communication among experts in biologics, small molecules, cell and gene therapy, and digital, IT, and AI drug discovery teams.
Benefits
- Medical, dental, and vision insurance.
- Generous paid time off options, including vacation and sick time, plus national holidays and a year-end shutdown.
- 401(k) match and annual company contribution.
- Company-paid life insurance.
- Annual corporate bonus and quarterly sales incentive for eligible positions.
- Long-term incentive plan for eligible positions.
- Company fleet vehicle for eligible positions.
- Referral bonus program.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
