Principal Scientist II, AI-Guided Antibody Drug Conjugate Design

This role will integrate computational biology, antibody engineering, linker-payload chemistry, and translational drug discovery to create ADCs with improved efficacy, safety, and manufacturability.

The successful candidate will collaborate across biologics, medicinal chemistry, data science, and translational research teams to design and optimize antibody architectures, conjugation strategies…

Develop and implement AI/ML models to guide ADC discovery and optimization, including target selection, antibody engineering, linker design, and payload selection.

Build predictive models for critical ADC properties, including stability, internalization, efficacy, pharmacokinetics, toxicity, and therapeutic index.

PhD in computational biology, bioengineering, protein engineering, chemistry, chemical biology, pharmaceutical sciences, or a related discipline.

Demonstrated expertise in antibody engineering, including humanization, affinity maturation, format engineering, and developability optimization.

Proven track record applying machine learning, deep learning, generative AI, or computational design methods to therapeutic discovery.

Strong understanding of ADC pharmacology, intracellular trafficking, pharmacokinetics, safety drivers, and resistance mechanisms.