Principal Scientist, Computational Protein Design
Moderna · Cambridge, Massachusetts ·
- Seniority
- Principal
- Employment
- Full time
- Category
- Design
- Experience
- 5+ years
- Visa sponsorship
- No
- Company size
- 1000+
- Salary
- USD 142,500 – 256,500 / year
Moderna · Cambridge, Massachusetts ·
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Lead computational protein design for therapeutic antibodies and T-cell receptors using AI/ML, structural modeling, and experimental integration to optimize affinity, stability, and safety.
The Role:
Moderna’s Therapeutics Research group is seeking a talented, experienced, and highly motivated Principal Scientist to support computational protein design across therapeutic research. This role will focus primarily on the design and optimization of T cell receptors and antibodies, while also contributing to broader protein design efforts across a range of therapeutic modalities.
The successful candidate will bring deep expertise in protein structure, de novo binder design, molecular recognition, and state-of-the-art computational design methods and workflows. They will serve as a scientific and technical leader for computational binder design, helping to build a next-generation platform for the discovery, engineering, and optimization of TCRs and antibodies against defined targets. This individual will work in close partnership with structural biology, directed evolution, immunology, translational science, and program teams to advance platform innovation and therapeutic programs across Moderna’s Research and Early Development portfolio.
Here’s What You’ll Do
Lead and execute computational protein design campaigns across therapeutic research, with a focus on de novo binder design for TCRs and antibodies.
Drive computational binder optimization approaches to improve affinity, specificity, stability, expression, cognate pairing efficiency, potency, developability, sequence liabilities, and compatibility with mRNA-expressed therapeutic formats.
Help build an integrated computational-to-experimental design platform that connects generative design, docking, interface scoring, rational library design, display or functional screening, next-generation sequencing, and active-learning cycles.
Establish computational off-target screening strategies for engineered TCRs and other binders, including structural motif scanning, alloreactivity risk assessment, counterselection logic, and prioritization of candidates for experimental validation.
Partner with cross-reactivity, microbial display, directed evolution, structural biology, functional assay, and program teams to convert model outputs into experimental data and incorporate assay results into iterative model improvement.
Evaluate, deploy, and advance state-of-the-art computational methods, including structure prediction, inverse folding, diffusion- or flow-based generation, protein language models, molecular docking, molecular dynamics, interface scoring, and multi-objective optimization.
Identify external technologies, datasets, software capabilities, and strategic partnerships that accelerate computational protein design workflows.
Monitor emerging literature and apply leading-edge methods in machine learning, predictive modeling, and protein engineering.
Extend protein design capabilities beyond binders where strategically valuable, including enzymes or catalytic scaffolds, DNA- or RNA-binding proteins, protein switches, engineered scaffolds, and other functional domains relevant to therapeutic platform concepts.
Here’s What You’ll Need (Basic Qualifications)
PhD in computational biology, protein engineering, bioinformatics, structural biology, biophysics, or a closely related discipline.
At least 5 years of post-graduate experience in computational protein design, with a demonstrated track record in de novo binder generation and optimization using AI/ML-guided and structure-informed design approaches.
Demonstrated experience connecting computational design strategies to experimental validation and optimization workflows.
Experience leading or contributing to discovery programs that require alignment across computational biology, AI/ML, data engineering, structural biology, immunology, translational science, preclinical development, external partners, and senior scientific stakeholders.
Strong publication record or equivalent record of scientific impact in computational protein design, structural biology, protein engineering, or a related field.
Technical fluency with modern computational protein design and structural modeling tools, such as AlphaFold, AlphaFold-Multimer, Rosetta, PyRosetta, RFdiffusion, ProteinMPNN, and related models.
Experience mentoring scientists, managing at least one direct report, or providing scientific leadership in a dynamic research environment.
Excellent written, presentation, and interpersonal communication skills, including the ability to translate complex technical tradeoffs into clear recommendations for scientific and executive audiences.
Here’s What You’ll Bring to the Table (Preferred Qualifications)
Over 5 years of post-graduate experience in computational protein design, with a strong record of de novo binder generation and optimization and peer reviewed publications.
Direct experience with TCR design or TCR therapeutic engineering.
Strong understanding of TCR structure and function, HLA restriction, cross-reactivity, alloreactivity, and the safety constraints involved in engineering therapeutic TCRs.
Experience implementing modern machine learning methods and innovative software workflows to keep pace with advances in computational protein design.
Ability to work directly with computational scientists and AI/ML teams using Python-based workflows and modern machine learning infrastructure.
Experience building computational specificity, developability, and off-target screening workflows.
Familiarity with experimental validation methods that support protein or TCR design, such as yeast, mammalian, or phage display; deep mutational scanning; tetramer or multimer binding assays; developability assays; and cell-based functional assays.
Ability to evaluate protein design opportunities beyond binder discovery, including enzymes or catalysts, DNA- or RNA-binding proteins, CAR signaling domains, engineered scaffolds, switches, sensors, or intracellular functional proteins.
Demonstrated ability to operate as both a technical individual contributor and a cross-functional scientific partner in a fast-paced, program-driven environment.
Pay & Benefits
At Moderna, we believe that when you feel your best, you can do your best work. That’s why our benefits and well-being resources are designed to support you—at work, at home, and everywhere in between.
About Moderna
Since our founding in 2010, we have aspired to build the leading mRNA technology platform, the infrastructure to reimagine how medicines are created and delivered, and a world-class team. We believe in giving our people a platform to change medicine and an opportunity to change the world.
By living our mission, values, and mindsets every day, our people are the driving force behind our scientific progress and our culture. Together, we are creating a culture of belonging and building an organization that cares deeply for our patients, our employees, the environment, and our communities.
We are proud to have been recognized as a Science Magazine Top Biopharma Employer, a Fast Company Best Workplace for Innovators, and a Great Place to Work in the U.S.
If you want to make a difference and join a team that is changing the future of medicine, we invite you to visit modernatx.com/careers to learn more about our current opportunities.
Our Working Model
As we build our company, we have always believed an in-person culture is critical to our success. Moderna champions the significant benefits of in-office collaboration by embracing a 70/30 work model. This 70% in-office structure helps to foster a culture rich in innovation, teamwork, and direct mentorship. Join us in shaping a world where every interaction is an opportunity to learn, contribute, and make a meaningful impact.
Moderna is a smoke-free, alcohol-free, and drug-free work environment.
Equal Opportunities
Moderna is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry or citizenship, ethnicity, disability, military or protected veteran status, genetic information, sexual orientation, marital or familial status, or any other personal characteristic protected under applicable law. Moderna is a place where everyone can grow. If you meet the Basic Qualifications for the role and you would be excited to contribute to our mission every day, please apply!
Moderna is an E-Verify Employer in the United States. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.
Accommodations
We’re focused on attracting, retaining, developing, and advancing our employees. By cultivating a workplace that values diverse experiences, backgrounds, and ideas, we create an environment where every employee can contribute their best.
Moderna is committed to offering reasonable accommodations to qualified job applicants with disabilities. Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should contact the Accommodations team at [email protected].
Export Control Notice
This position may involve access to technology or data that is subject to U.S. export control laws, including the Export Administration Regulations (EAR). As such, employment is contingent upon the applicant’s ability to access export-controlled information in accordance with U.S. law. Due to the nature of the work and regulatory requirements, only individuals who qualify as U.S. persons (citizens, permanent residents, asylees, or refugees) are eligible for this position. For this role Moderna is unable to sponsor non-U.S. persons to apply for an export control license.
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