Overview In this Principal Scientist role, you lead computational protein design campaigns focused on de novo binders for TCRs and antibodies within Moderna's Therapeutics Research group. You will help build an integrated design platform bridging computation and experiments to advance antibody and TCR programs. You'll work with cross-functional teams to scale platform capabilities and improve developability and safety profiles for therapeutic modalities. This is a high-impact role at the forefront of protein design and mRNA-enabled therapies.
Compensation / Benefits- competitive healthcare
- well-being programs (fitness, mindfulness, mental health)
- family planning benefits
- generous paid time off
- discretionary year-end shutdown
- equity or incentive awards (subject to plan eligibility)
Responsibilities- Lead computational protein design campaigns for de novo binder design of TCRs and antibodies
- Advance binder optimization to improve affinity, specificity, stability, expression, and developability for mRNA-expressed formats
- Contribute to an integrated computational-to-experimental design platform (generative design, docking, interface scoring, library design, screening, sequencing, active-learning)
- Establish off-target screening for engineered TCRs and binders, including cross-reactivity and alloreactivity risk assessment
- Collaborate with cross-functional teams to convert model outputs into experimental data and iteratively improve models
- Evaluate and adopt state-of-the-art methods (structure prediction, docking, MD, ML, multi-objective optimization)
- Identify external technologies and partnerships to accelerate design workflows
- Monitor literature and apply cutting-edge ML and protein engineering methods
- Extend design capabilities beyond binders to other functional proteins and domains
Key requirements- PhD in relevant field
- At least 5 years of post-graduate experience in computational protein design with de novo binder generation and AI/ML-guided design
- Experience linking computational design to experimental validation and optimization
- Experience leading or contributing to discovery programs with cross-functional alignment
- Strong publication record or equivalent impact in related fields
- Technical fluency with AlphaFold, AlphaFold-Multimer, Rosetta, PyRosetta, RFdiffusion, ProteinMPNN
- Experience mentoring or managing at least one direct report
- Excellent communication skills for scientific and executive audiences
- cross-functional collaboration
- clear scientific communication
- ability to translate complex tradeoffs into actionable guidance
- AlphaFold
- AlphaFold-Multimer
- Rosetta
