Associate Principal Scientist, AI and Computational Tools, Oncology R&D (1-year FTC)
AstraZeneca2 hours ago
Cambridge, United KingdomStaff+
Responsibilities
- Lead the design, development, deployment, and lifecycle management of AI-powered tools and workflows, including data-wrangling pipelines, visualization applications, agentic AI solutions, and LLM-integrated tools.
- Develop and evolve structured, quality-controlled, reproducible data infrastructure and standards for the discovery group.
- Act as an AI Architect and technical subject matter expert by defining best practices, guiding technology choices, and driving adoption of reusable code, packages, and tools.
- Lead AI and computational capability projects addressing strategic scientific challenges while balancing feasibility, governance, sustainability, and user adoption.
- Develop agentic workflows to extract biological insight from single-cell, spatial transcriptomics, functional screening, and multiomic datasets.
- Mentor colleagues, support adoption of AI-enabled and reproducible workflows, and lead collaborations with Data Science, R&D IT, and platform teams.
- Prepare scientific and technical presentations, maintain accurate electronic laboratory notebook records, and ensure compliance with internal standards and external regulations.
Requirements
- Experience leading complex computational or AI initiatives from concept through implementation, deployment, and adoption in a scientific environment.
- Experience with agentic AI frameworks, LLM integration, or AI-assisted coding tools such as GitHub Copilot or Claude Code in research or production.
- Experience developing and deploying tools for others, such as Shiny applications, automated reporting systems, or shared analysis packages, with version control and collaborative software-development practices.
- Experience building research data infrastructure using approaches such as LIMS schemas, electronic laboratory notebook workflows, structured databases, or reproducible data pipelines with automated validation and quality control.
- Strong proficiency in Python and/or R and experience with large-scale data management.
- Ability to drive adoption of computational capabilities through user engagement, documentation, training, and communication with scientific leadership.
- Evidence of influencing scientific or technical direction through technical leadership, best-practice development, mentoring, or capability building.
- Strong collaboration skills and experience working across wet-lab and dry-lab teams in a matrixed environment.
- Experience preparing written scientific reports and delivering oral presentations.
- PhD in a relevant discipline or equivalent experience is desirable.
- Experience with graph neural networks, transformers, probabilistic models, Domino, QuartzBio, and biological datasets in immunology or oncology is desirable.
Benefits
- One-year fixed-term contract based in Cambridge, UK.
- Opportunity to work at the intersection of oncology discovery, AI, data engineering, and immunology with scientists generating novel experimental data.
- Opportunity to shape AI-enabled, practical, and reproducible discovery workflows across Oncology R&D.
Tech Stack
Categories
AI ApplicationsData Engineering
About AstraZeneca
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