Associate Principal Scientist, Ai For Chemical Toxicology
AstraZeneca
Not specified; further clarification needed on remote or onsite requirements.
Phd in chemoinformatics or bioinformatics
Strong ai/ml experience with pytorch tensorflow
Advanced python or r programming skills
AstraZeneca is seeking an Associate Principal Scientist in AI for Chemical Toxicology to lead the development of predictive safety modeling using AI, chemoinformatics, and bioinformatics. The ideal candidate will possess a PhD in a related field, strong AI/ML skills, and experience in integrating multimodal data, while contributing to the scientific leadership and innovation within drug development processes
Job Summary
The role involves leading next-generation predictive safety modeling at scale by integrating chemical and biological data to inform risk assessment.
Candidates will develop, optimize, and deploy predictive safety models using cutting-edge AI approaches and machine learning techniques.
This fully hands-on computational role requires cross-functional scientific leadership and the ability to mentor junior scientists.
Matching Summary
Match Score: 85
AstraZeneca is seeking an Associate Principal Scientist in AI for Chemical Toxicology to lead the development of predictive safety modeling using AI, chemoinformatics, and bioinformatics. The ideal candidate will possess a PhD in a related field, strong AI/ML skills, and experience in integrating multimodal data, while contributing to the scientific leadership and innovation within drug development processes.
Skills & Requirements
Must-have
PhD in Chemoinformatics or Bioinformatics
Strong AI/ML experience with PyTorch TensorFlow
Advanced Python or R programming skills
Experience with multimodal biological chemical datasets
Proven leadership in delivering impactful modeling work
Nice-to-have
Experience with Safety Omics Cell Painting imaging data
Background in toxicology pharmacology or ADME
Experience with cloud computing or workflow automation
Track record of publications in top AI conferences
Experience supervising scientists or managing collaborations
Key Requirements
PhD in Chemoinformatics Bioinformatics Computational Toxicology or related field
Familiarity with GitHub CI/CD pipeline and MLOps practices
Excellent communication and stakeholder engagement skills