AIDD Principal Scientist

Key Responsibilities:

>Define AI-driven drug discovery roadmap, pioneer next-generation computational paradigms covering target mechanism elucidation to preclinical candidate delivery

Architect multimodal biomedical data processing frameworks, develop proprietary intelligent drug discovery systems enabling high-throughput data fusion & knowledge inference.

>Breakthrough technical barriers in generative AI applications for drug R&D, innovate core algorithm modules including molecular design, 3D structure modeling, and virtual screening.

>Establish technical standards for AI-HPC integrated computing platforms, optimize technology transfer path from prototypes to production systems.

>Lead cross-sector collaborations to build algorithm-experiment-clinical validation loops, advance AI-discovered candidates to IND-enabling stages.

>Serve as key technical advisor for regulatory-compliant AI implementation per FDA/CFDA guidelines.

Qualifications:

>Ph.D. in Computer Science/Computational Biology/Chemoinformatics with +5 years in AI drug discovery core algorithm development

>Original contributions in generative models, geometric DL, or multi-task learning (top-tier publications/patents)

>Hands-on experience in 2+ complete drug discovery projects from target validation to lead optimization

>Expert in AI industrialization with large-scale distributed system design (100+ nodes)

>Recognized technical authority with NeurIPS/ICML committee roles or standard-setting participation.

>Deep understanding of technological trends in drug discovery with successful enterprise implementations

>Experience in AI-CRO collaborations or preclinical technical integration

>Proficiency in molecular simulations (FEP, QM/MM)

>Cloud-native AI development expertise with MLOps platform building

>Agile development certifications (PMP/Scrum)