Working at the intersection of Computational Drug Design, project teams, Data & Methods, and Digital Technology & Engineering, this individual will leverage deep expertise in computational chemistry, cheminformatics, and AI-driven drug discovery to identify high-value opportunities across the design-make-test-analyze (DMTA) cycle and translate them into scientifically rigorous AI co-scientists that enhance compound design, knowledge synthesis, data interpretation, hypothesis generation, and decision-making. Partner with project teams and scientific leaders to develop and deploy AI co-scientists that support knowledge synthesis, SAR analysis, scientific question answering, experiment planning, virtual screening, molecular design, and lead optimization, leveraging established computational chemistry and cheminformatics approaches alongside modern AI methods.