Senior Director, CADD​/AIDD

Responsible for the overall strategic planning, team building, and technical execution of the company's computer-aided drug design (CADD) capabilities. Core strengths center on structure-based drug design, molecular simulation, and virtual screening, while also steering the application of AI-driven drug design (AIDD) methods across the pipeline. Drives deep collaboration between the computational team and Chemistry, Biology, DMPK, and other functions to accelerate hit discovery and lead optimization and to shorten discovery timelines.

• Define the company's CADD/AIDD technical roadmap and annual work plan, balancing investment between traditional computational chemistry methods and emerging AI approaches
• Build, develop, and manage a computational chemistry / computational biology team; establish a tiered development framework and technical review mechanisms
• Oversee planning and budgeting for computational infrastructure (workstations, GPU clusters, commercial software licenses, cloud computing resources)

• Lead structure-based drug design (SBDD): homology modeling, molecular docking, binding-mode prediction, binding-pocket analysis
• Lead the application of molecular dynamics (MD) simulation, free-energy perturbation (FEP/TI), and other quantitative prediction methods from hit through lead optimization
• Organize and gatekeep virtual screening strategies (structure-based and ligand-based) and compound library design to improve hit rates
• Evaluate and drive validated application of AI/deep learning methods (e.g., structure prediction, generative molecular design, property prediction models) in the pipeline, judging their incremental value relative to traditional methods
• Establish and optimize computational workflows for ADMET property prediction and drug-likeness assessment

• Serve as the computational lead in project initiation reviews and milestone decisions across multiple drug discovery programs, providing computational judgment and recommendations on compound design
• Work closely with Chemistry, Biology, Structural Biology, and DMPK teams to close the loop between computational predictions and experimental validation, continuously calibrating model reliability
• Represent the computational team in BD/due diligence and technical evaluation of partnering opportunities

• Track frontier CADD/AIDD methods and tools, assessing their value for adoption
• Represent the company's computational drug design capabilities at industry conferences and in partnership discussions

• PhD in Chemistry, Computational Chemistry, Computational Biology, Biophysics, or a related field
• 10+ years of industry experience in computational drug design at pharmaceutical/biotech companies, including at least 3–5 years of team management, with experience building a computational team from scratch or significantly scaling one
• Deep theoretical grounding in structure-based drug design; proficiency in at least one mainstream docking package (Glide/GOLD/Auto Dock, etc.) and homology modeling tools
• Hands-on expertise with MD simulation software (Desmond/GROMACS/AMBER/NAMD, etc.) and free-energy methods (FEP+/TI), with demonstrated experience supporting compound optimization decisions in real projects
• Solid virtual screening project experience; has led multiple end-to-end cases from virtual screening through wet-lab validation to hits/leads
• Experience driving practical application of AI/machine learning methods (structure prediction, generative design, property prediction) in drug discovery pipelines, with an understanding of their limitations and appropriate use cases
• Ability to translate computational results into…