Principal Scientist, TCR Optimization

The Role

The Therapeutics Research group at Moderna is seeking a talented, experienced, and highly motivated Principal Scientist to build, optimize, and execute T cell receptor optimization workflows for next-generation TCR-based therapeutics. This individual will lead the development of scalable experimental platforms to improve key TCR properties, including affinity, cross‑reactivity, stability, expression, develop ability, functional potency, and compatibility with mRNA‑expressed therapeutic formats. The successful candidate will apply deep expertise in display‑based protein engineering, TCR biology, biophysical characterization, cross‑reactivity screening, and functional assays to advance TCR candidates through iterative wet‑lab and computational optimization.

This candidate will work closely with cross‑functional partners in TCR discovery, protein engineering, computational biology, AI/ML, functional assay development, translational science, and preclinical development. The role is well suited for a hands‑on scientist who can execute complex experimental workflows, interpret multi‑parameter datasets, and contribute to the generation of optimized TCR candidates with the potency, specificity, and develop ability required for therapeutic advancement.

• Build, optimize, and execute scalable TCR optimization workflows using display technologies and directed evolution approaches to improve affinity, specificity, stability, expression, develop ability, and therapeutic‑format compatibility.
• Establish an end‑to‑end TCR optimization pipeline that connects library design, display‑based screening, candidate recovery, sequence analysis, molecular characterization, functional validation, and lead selection.
• Design rational and semi‑rational TCR libraries informed by sequence, structure, pHLA biology, cross‑reactivity risk, develop ability considerations, and therapeutic‑format requirements.
• Lead multi‑parameter and iterative optimization campaigns that balance affinity, specificity, stability, expression, develop ability, functional potency, and safety‑related risk.
• Partner with computational scientists to incorporate TCR cross‑reactivity, structural modeling, sequence‑function relationships, and develop ability data into iterative optimization decisions.
• Interpret complex screening, binding, biophysical, and functional datasets to prioritize candidates and recommend optimization strategies.
• Support current and future TCR therapeutic programs by delivering optimized binders suitable for therapeutic evaluation, including TCR‑T, TCR engager, and other TCR‑based modalities.
• Evaluate and implement new display, screening, automation, and protein engineering technologies that can improve throughput, specificity, scalability, or candidate quality.
• Collaborate with AI/ML, NGS, functional assay, reagent generation, preclinical, and external partner teams to ensure optimization workflows generate high‑quality, decision‑ready data.
• Communicate scientific strategy, experimental results, technical risks, tradeoffs, and recommendations to multidisciplinary project and platform teams.

• PhD in immunology, protein engineering, molecular biology, biochemistry, biophysics, cell biology, or related disciplines.
• At least 5 years of post‑PhD experience in TCR engineering, protein engineering, directed evolution, display‑based screening, or a closely related therapeutic discovery discipline.
• Demonstrated experience executing TCR or TCR‑mimetic optimization workflows that connect binding, stability, expression, develop ability, and functional potency data.
• Hands‑on experience with display technologies, rational or semi‑rational library design, affinity maturation, specificity engineering, and develop ability optimization.
• Experience designing and interpreting binding, stability, expression, functional potency, or biophysical characterization assays.
• Demonstrated ability to lead complex experimental workflows, troubleshoot technical challenges, and deliver high‑quality datasets under active program timelines.
• Experience collaborating with computational biology, AI/ML, NGS, reagent…