Design, implement, train, and iterate on novel deep learning models for TCR–pMHC specificity prediction.
Extend and adapt advances in protein language models, structure prediction, generative modeling, and representation learning to the immune receptor setting.
Utilize scalable training infrastructure to support large-scale model development and experimentation.
Conduct rigorous benchmarking and evaluation strategies to ensure models are scientifically sound and practically superior.
Translate biological principles of T cell recognition into principled modeling decisions.
Influence large-scale experimental data generation to maximize modeling leverage and long-term performance gains.
Provide input and technical recommendations to broader modeling discussions and roadmap planning.
Work closely with computational biology, immunology, translational, and engineering teams to ensure models are robust, reproducible, and aligned with overall product goals.
Communicate modeling insights, approaches, and results to cross-functional scientific audiences.
Contribute to publications, presentations, etc. through technical execution and analysis.

Requirements

PhD in a quantitative discipline (e.g. Machine Learning, Computational Biology, Computer Science) + 5 years progressive experience applying machine learning to real-world scientific or biological problems OR equivalent combination of education and experience.
Progressive experience in the development and deployment of deep learning methods
Strong hands-on experience in python and modern ML tooling (PyTorch preferred)
Strong experience in deep learning architecture design and implementation.
Experience working with large datasets and high-performance computing environments
Ability to independently define, scope, and execute complex technical research problems.
Strong written and verbal communication skills, with ability to present highly technical material to diverse audiences.
Demonstrated ability to collaborate effectively in cross-functional, multi-disciplinary teams
Driven by impact: motivated to see models transition from research to clinical and commercial application.

Benefits

equity grant
bonus eligible

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

deep learningmachine learningprotein language modelsstructure predictiongenerative modelingrepresentation learningmodel evaluationdata generationpythondeep learning architecture

Soft Skills

communicationcollaborationindependent problem solvingtechnical recommendationspresentation skillscross-functional teamworkimpact-driven mindset

Certifications

PhD in quantitative discipline