Location:
Beijing or Shanghai
Department:
R&D / Drug Discovery
Reports To:
SVP of Research
About the Role
We are seeking an innovative and experienced
Head of CADD
to lead our computational chemistry, AI/ML-driven molecular design efforts. You will oversee the integration of cutting-edge computational methods (e.g., molecular modeling, structure-based design, ligand-based design, AI/ML, and molecular dynamics) to accelerate the identification and optimization of novel therapeutics across multiple therapeutic areas.
Key Responsibilities
- Define and execute the CADD strategy to support small-molecule, biologics, or nucleotide-based drug discovery programs.
- Collaborate with cross-functional teams (medicinal chemistry, biology, pharmacology/translational medicine, DMPK, clinical development) to drive hit-to-lead and lead optimization.
- Evaluate and implement emerging computational tools (e.g., AI/ML, quantum computing, cloud-based platforms) to enhance drug design efficiency.
- Lead
in silico
drug design efforts: - Structure- and ligand-based virtual screening.
- Molecular docking, homology modeling, and free-energy calculations.
- Pharmacophore modeling, QSAR, and cheminformatics.
- AI/ML model development for target prediction, ADMET, and compound prioritization.
- Oversee the analysis of large-scale omics data (genomics, proteomics) for target identification.
- Guide the use of molecular dynamics simulations and fragment-based drug design.
- Manage and mentor a team of computational chemists, bioinformaticians, and data scientists.
- Foster collaborations with CROs, academic partners, and AI/ML vendors.
- Present computational insights to stakeholders and contribute to IP filings/publications.
- Stay abreast of advancements in CADD, AI/ML, and structural biology.
- Champion the adoption of new technologies (e.g., generative chemistry, active learning).
Education & Experience
- PhD
in Computational Chemistry, Bioinformatics, Pharmaceutical Sciences, or related fields. - 10+ years
in CADD (industry experience preferred), with a track record of contributing to drug discovery pipelines. - Proven leadership experience managing high performance teams.
- Expertise in CADD tools:
Schrödinger, MOE, OpenEye, GROMACS, Rosetta, etc. - Proficiency in programming/scripting (Python, R, Perl) and ML frameworks (TensorFlow, PyTorch).
- Familiarity with
HPC, cloud computing (AWS/GCP), and data visualization tools
. - Strong communication and cross-functional collaboration abilities.
- Entrepreneurial mindset with problem-solving agility.
Preferred Qualifications
- Experience with
biologics design
(antibodies, RNA-targeting therapeutics) is a plus. - Knowledge of
clinical biomarkers and translational informatics
. - Contributions to patents or peer-reviewed publications in CADD.