Introduction to the Role
This position focuses on guiding AI research that converts complex, multimodal data into decisions to accelerate drug development and improve patient outcomes. It is a fantastic opportunity to thrive in an environment where bold ideas evolve into deployed models and peer-reviewed science, working alongside leading scientists, engineers, and product leaders!
As the Director of EAI, AI Research, the objective is to lead a high-calibre, interdisciplinary team advancing machine learning across multiple therapeutic areas. The role entails setting the research agenda, inventing new methods, and transforming prototypes into robust, governed solutions that support imaging, diagnostics, and clinical validation pipelines. This offers a unique chance to build strategy from the ground up while staying hands-on with cutting-edge methodologies.
Accountabilities
- Research Strategy: Lead the roadmap for priority problem spaces, supporting teams to develop high-value AI capabilities using modern engineering standards.
- Multimodal ML Innovation: Invent and apply methods in deep, representation, reinforcement, and active learning, tailoring metrics to domain-specific challenges.
- Translational Pipeline Impact: Convert scientific advances into production-grade models that improve decision quality and automate key discovery steps.
- ML Ops and Governance: Establish robust practices for model tracking, governance, and lifecycle management, ensuring responsible AI use.
- Cross-Functional Partnership: Advise and co-create with partners across therapeutic areas, translating business needs into effective ML solutions.
- Scientific Contribution: Mentor researchers, publish in top-tier venues, and represent AstraZeneca at leading conferences!
- Stakeholder Alignment: Maintain clear, multidirectional communication across the organisation regarding goals, risks, and results.
Essential Skills and Experience
- Academic Background: PhD in computer science, statistics, applied mathematics, or a related area (or an MSc with 5 years of relevant background).
- Industry Experience: Minimum of 2 years developing machine learning models in an industry setting.
- Machine Perception: Expertise with methods in at least one relevant modality, alongside explainability techniques.
- Domain Application: Experience applying AI to fields such as pathology imaging, radiological analysis, diagnostics, prognostics, or clinical Quality Control.
- ML Ops Knowledge: Practical experience with model tracking, governance, and managing multiple models in diverse production contexts.
- Technical Leadership: Proven ability to lead teams through complex scientific and research efforts.
Desirable Skills and Experience
- Publication Record: A strong research programme demonstrated by prestigious publications (e.g., Nature Machine Intelligence, NeurIPS, ICML) with at least one as lead author.
- Domain Expertise: Deep understanding of the drug development or clinical trial processes.
- Collaborative Delivery: A track record of successfully working with AI engineering teams to deploy complex predictive algorithms.
Working Environment
- Collaborative Culture: Bringing unexpected teams together sparks bold thinking. To facilitate this, we operate on a hybrid model, working an average of three days per week from the office while respecting individual flexibility.
Why AstraZeneca
AstraZeneca pairs cutting-edge AI with profound scientific depth to deliver life-changing insights. The culture emphasises continuous learning, ethical standards, and doing things the right way. Access to rich, diverse datasets provides the foundation to build advanced enterprise analytics.
Equal Opportunity and Accommodations
AstraZeneca is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.
Call to Action
If the prospect of leading breakthrough AI research and converting it into tangible patient outcomes excites you, apply today to drive what comes next!
#EAI
Date Posted
18-May-2026
Closing Date
31-May-2026
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.
