Senior Scientist - Computational Protein Design

About the role

In this vital role you will develop and deploy automated computational pipelines for large-scale binder design, supporting the creation of diverse design candidates and libraries across multiple targets. Your work will directly enable discovery efforts by accelerating the generation of molecules used to probe novel biology and deliver new biological insights.

Key Responsibilities

• Develop and automate ML protein design workflows for binder generation
• Build scalable pipelines for designing large libraries of de novo proteins across multiple targets
• Apply computational methods to support multiplexed screening strategies and receptor discovery efforts
• Design and prioritize binders for individual targets and large target panels
• Contribute to shared tools, workflows, and best practices within the protein design community
• Collaborate closely with experimental scientists and data teams to enable rapid validation and iteration

Qualifications

Basic Qualifications:

• Doctorate degree PhD OR PharmD OR MD and relevant post-doc experience in Computational Biology, Structural Biology, Bioengineering, Biophysics, Computer Science, or related discipline with a focus on protein design
• OR Masters degree and 3 years of protein design experience
• OR Bachelors degree and 5 years of protein design experience

Preferred Qualifications:

• Ph.D. with postdoc in Computational Biology, Structural Biology, Bioengineering, Biophysics, Computer Science, or related discipline with a focus on protein design
• Demonstrated experience in computational protein design, including the design of binders such as minibinders and/or antibodies
• Experience developing automated and scalable computational pipelines for protein design or structural modeling, ideally in high-throughput environments
• Familiarity with modern AI/ML-driven protein design and structure prediction tools (e.g., AlphaFold, ProteinMPNN, RFdiffusion, or similar frameworks)
• Strong programming skills in Python and/or other scripting languages, with experience building maintainable workflows and automation for large-scale computational experiments
• Experience working with large protein libraries or multiplexed design strategies, including design filtering, ranking, and diversity optimization
• Knowledge of protein structure-function relationships, epitope targeting strategies, and protein-protein interaction design principles
• Experience integrating computational design outputs with experimental validation workflows, including library generation, screening, or directed evolution approaches
• Familiarity with cloud computing, high-performance computing (HPC), and workflow orchestration tools
• Experience collaborating in cross-functional teams spanning computational scientists, experimental biologists, and data scientists
• Strong communication skills and ability to contribute to a collaborative protein design community, including sharing tools, best practices, and design insights

What you can expect from us

As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.