Senior Scientist, – AI and Computational Tools, Oncology R&D (12-Month FTC)
Location: Cambridge, UK.
Salary: Competitive + Excellent Employee Benefits!
Introduction to the Role:
At AstraZeneca, we turn ideas into life changing medicines. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. We’re passionate about the potential of science to address the unmet needs of patients around the world. We commit to those areas where we believe we can really change the course of medicine and bring big new ideas to life.
AstraZeneca’s vision in Oncology is to push the boundaries of science to change the practice of medicine, transform the lives of patients living with cancer, and to ultimately eliminate cancer as a cause of death.
Are you ready to work on one of the most exciting pipelines in the Oncology industry?
About the Role:
We are seeking a highly motivated, independent, collaborative Senior Scientist to join our Immune Cell Engagers Discovery group in Cambridge, UK. This role sits at the intersection of applied AI, computational data science, and immuno-oncology biology, and is central to how we build and embed AI-first workflows across our discovery department.
You will combine strong programming and data engineering skills with immunology domain expertise to design and deploy AI-powered tools, build robust data infrastructure, and act as a key AI Architect for the group. You will work closely with wet-lab scientists, data science teams, and R&D IT to translate experimental data into scalable, reproducible, and insight-generating systems. Critically, you will mentor and upskill colleagues across the department, helping to embed AI fluency at every level of the team.
Main Duties and Responsibilities
In this computational role within the Immune Cell Engagers Discovery group, you will:
Design, develop, and deploy AI-powered tools and workflows for the discovery group, including data wrangling pipelines, visualisation apps, agentic AI solutions, and LLM-integrated tools that accelerate experimental decision-making and reduce manual analytical burden.
Build and maintain data infrastructure to centralise, standardise and quality control experimental data from functional cell biology assays and multi-omic platforms, design and implement LIMS schemas, electronic lab notebook (ELN) workflows, and structured databases to ensure data is FAIR, reproducible and downstream-ready.
Act as an AI Architect for the department — defining best practices for AI tool use, contributing to department-wide AI strategy, and building reusable code, packages, and tools that can be adopted broadly by the team.
Interface with Data Science, R&D IT, and external platform teams to co-develop scalable solutions, contribute to shared infrastructure and ensure tools meet both scientific and engineering standards.
Develop and apply ML and statistical models to extract biological insight from high-dimensional datasets, including single-cell and spatial transcriptomics, functional screening data, and multi-omic integration.
Contribute to the generation, understanding, and assessment of biological datasets related to functional cell biology assays and multi-omic data to generate insights relevant to drug development in the Immune Cell Engagers Discovery group.
Essential Requirements
Familiarity with agentic AI frameworks, LM integration, or AI-assisted coding tools (e.g. GitHub, Copilot, Claude Code, or similar) in a research or production context.
Hands-on experience developing and deploying tools for use by others – such as Shiny apps, automated reporting systems, or shared analysis packages; comfort with version control (Git/GitHub) and collaborative software development practices.
Experience with single-cell and spatial transcriptomics, bulk RNA-seq, and/or functional screening datasets; ability to build robust analytical pipelines and/or QC processes. Demonstrated ability to train users and drive adoption of new data systems or tools across research teams, including writing documentation and presenting to scientific leadership.
Desirable Skills
PhD in relevant disciplines or equivalent experience (e.g. Bioinformatics, Systems Biology, Computational Biology, Applied Mathematics, Statistics, Data Science, Computer Science).
Expertise in T-cell engagers, cytokines, bispecific molecules, tumour microenvironment and/or myeloid biology.
What You Will Gain
You will operate at the cutting edge of oncology discovery, combining AI and data engineering with deep immunology to accelerate target discovery, mechanism-of-action studies, and candidate selection. You will play a central role in shaping how the Immune Cell Engagers Discovery group integrates AI into its daily workflows – building tools that colleagues rely on, mentoring the next generation of computationally-enabled scientists, and helping define what an AI-first discovery department looks like in practice.
So, what’s next?
Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you!
Where can I find out more?
Our Social Media,
- Follow AstraZeneca on LinkedIn: https://www.linkedin.com/company/1603/
- Follow AstraZeneca on Facebook: https://www.facebook.com/astrazenecacareers/
- Follow AstraZeneca on Instagram: https://www.instagram.com/astrazeneca/?hl=en
Date Posted
05-Jun-2026
Closing Date
18-Jun-2026
Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.
