Hybrid (minimum of three days in the office per week)
Machine learning and ai solutions
Transcriptomics and proteomics data analysis
Python and ai libraries (tensorflow, pytorch)
AstraZeneca is seeking an Associate Director, AI to lead the design and deployment of advanced machine learning and AI solutions for drug development and discovery. The role involves collaboration with scientists and stakeholders to enhance bioinformatics processes, particularly in toxicological safety, while fostering a culture of innovation and flexibility within the team
Job Summary
The Predictive AI and Data team provides AI and Bioinformatics solutions to accelerate drug development and discovery by leveraging company data and cutting-edge AI approaches.
As Associate Director, AI, you will be accountable for hands-on design and deployment of advanced Machine Learning and AI solutions for processing, analysis, and interpretation of biological data within toxicological safety domains.
Join a collaborative environment where curiosity and courage meet practical impact, combining digital, data science, and AI with deep biological insight to tackle complex disease and shape the future of healthcare.
Matching Summary
Match Score: 85
AstraZeneca is seeking an Associate Director, AI to lead the design and deployment of advanced machine learning and AI solutions for drug development and discovery. The role involves collaboration with scientists and stakeholders to enhance bioinformatics processes, particularly in toxicological safety, while fostering a culture of innovation and flexibility within the team.
Skills & Requirements
Must-have
Machine Learning and AI solutions
Transcriptomics and proteomics data analysis
Python and AI libraries (TensorFlow, PyTorch)
Cloud environment (AWS)
Software development principles
Communication and presentation skills
Nice-to-have
Predicting compound safety
Life sciences experience
Agile team experience
Machine vision models familiarity
Key Requirements
PhD or equivalent experience
Proven AI/ML application in commercial context
Experience automating bioinformatics pipelines
Experience with large, high dimensionality datasets