(Senior) Principal / (Senior) Research Investigator, AI Drug Discovery (Small Molecules & Targeted Protein Degradation)

We are seeking a highly motivated Ph.D. expert with a profound scientific background and exceptional computational skills to join our AI Drug Discovery (AIDD) team. The successful candidate will accelerate the discovery and optimization of targeted protein degraders (TPD), traditional small molecules, and novel molecular modalities, while exploring new drug R&D paradigms in the AI era. Key Responsibilities: 1. Advancing AI Methodologies for Small Molecule Discovery • TPD-Focused AI Development: Develop AI tools specifically for Targeted Protein Degradation (TPD). • Molecular Generation & Optimization: Develop generative AI tools for de novo molecular generation, scaffold hopping, and multiparameter lead optimization. • Emerging Modalities: Monitor industry frontiers and actively prototype computational frameworks tailored for novel chemical modalities. 2. Cross-Functional Pipeline Enablement • Targeted Project Support: Deploy bespoke AI solutions to address project-specific bottlenecks. AI designed molecules with high synthetic tractability and actionable AI predictions to accelerate small molecule campaigns. Qualifications Education & Scientific Fundamentals: • Ph.D. in Computational Chemistry, Cheminformatics, Medicinal Chemistry, AI for Science, or a related field. • Strong grasp of organic chemistry and biology, coupled with foundational knowledge of the drug discovery lifecycle. Previous research or industry experience involving small molecule structural optimization is highly preferred. • Core Expertise (Must-have): Demonstrated track record in developing and deploying at least one of the following AIDD tools (evidenced by high-impact publications or successful pipeline implementation): -Molecular property and druggability prediction. -Molecular generation and multi-parameter optimization. -Compound-protein interation and affinity prediction. -Specialized tools for non-traditional small molecules. -LLMs for Medicinal Chemistry. Technical & Engineering Skills: • Proficient in Python, with extensive experience using cheminformatics libraries (e.g., RDKit, OpenBabel) and data processing stacks (e.g., Pandas, NumPy). • Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow); proficient in applying GNNs, Generative Models, Transformers, etc., to solve molecular problems. • Strong software engineering skills with the ability to lead the design and maintenance of complex AI tools. • Familiarity with traditional CADD computational methods (e.g., molecular docking, molecular dynamics simulations, free energy perturbation) is a plus. Soft Skills: • Fast Learner: Ability to quickly master existing AI tools, track industry advancements, and understand drug R&D workflows and technologies. • Independent Research: Strong capability to independently solve complex, cross-disciplinary R&D problems. • Communication: Excellent cross-disciplinary communication skills, capable of translating complex algorithmic logic into clear chemical and biological language. Preferred Qualifications: • 1-3+ years of practical industry experience supporting drug discovery pipelines. • Experience in building and integrating AI tool platforms tailored to drug discovery R&D scenarios. 申请职位 © 2023-2024 百济神州（北京）生物医药有限公司 京公网安备 11010802024479号京ICP备15060035号-3 招聘微信号 招聘微信号 招聘视频号 招聘视频号 官方微信号 官方微信号

ct publications or successful pipeline implementation): -Molecular property and druggability prediction. -Molecular generation and multi-parameter optimization. -Compound-protein interation and affinity prediction. -Specialized tools for non-traditional small molecules. -LLMs for Medicinal Chemistry. Technical & Engineering Skills: • Proficient in Python, with extensive experience using cheminformatics libraries (e.g., RDKit, OpenBabel) and data processing stacks (e.g., Pandas, NumPy). • Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow); proficient in applying GNNs, Generative Models, Transformers, etc., to solve molecular problems. • Strong software engineering skills with the ability to lead the design and maintenance of complex AI tools. • Familiarity with traditional CADD computational methods (e.g., molecular docking, molecular dynamics simulations, free energy perturbation) is a plus. Soft Skills: • Fast Learner: Ability to quickly master existing AI tools, track industry advancements, and understand drug R&D workflows and technologies. • Independent Research: Strong capability to independently solve complex, cross-disciplinary R&D problems. • Communication: Excellent cross-disciplinary communication skills, capable of translating complex algorithmic logic into clear chemical and biological language. Preferred Qualifications: • 1-3+ years of practical industry experience supporting drug discovery pipelines. • Experience in building and integrating AI tool platforms tailored to drug discovery R&D scenarios. 申请职位 © 2023-2024 百济神州（北京）生物医药有限公司 京公网安备 11010802024479号京ICP备15060035号-3 招聘微信号 招聘微信号 招聘视频号 招聘视频号 官方微信号 官方微信号