Associate Director, Ai

AstraZeneca

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Machine learning and ai solutions
Transcriptomics, proteomics, cell painting data
Python, tensorflow, pytorch
** AstraZeneca is seeking an Associate Director of AI to lead the design and deployment of machine learning solutions for analyzing biological data within toxicological safety domains. The role emphasizes collaboration with scientists and stakeholders to enhance drug development processes through AI technologies. **

Job Summary

  • The Predictive AI and Data team provides AI and Bioinformatics solutions across drug development and discovery stages, aiming to accelerate the process using cutting-edge AI approaches.
  • As Associate Director, AI, you will be responsible for hands-on design and deployment of advanced ML/AI solutions for processing and analyzing biological data, collaborating with global R&D hubs.
  • Join a collaborative environment where curiosity and courage meet practical impact, combining digital, data science, and AI with deep biological insight to tackle complex diseases and shape the future of healthcare.

Matching Summary

Match Score: 75

** AstraZeneca is seeking an Associate Director of AI to lead the design and deployment of machine learning solutions for analyzing biological data within toxicological safety domains. The role emphasizes collaboration with scientists and stakeholders to enhance drug development processes through AI technologies. **

Skills & Requirements

Must-have

  • Machine Learning and AI solutions
  • transcriptomics, proteomics, cell painting data
  • Python, TensorFlow, PyTorch
  • AWS or similar cloud environment
  • ML engineers and software developers
  • DevOps and MLOps practices

Nice-to-have

  • predict compound safety models
  • life sciences, healthcare, pharmaceutical industry
  • Agile team, product or platform-focused delivery

Key Requirements

  • PhD or equivalent experience
  • AI/ML in commercial context
  • Automate bioinformatics analysis pipelines
  • Large high dimensionality unstructured datasets
  • Software development and ML deployment principles
  • Leadership and project management skills
  • AI ethics and responsible AI practices

Work Rights

Not specified

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