Senior Scientist – AI and Computational Tools, Oncology R&D (12-Month FTC)

Senior Scientist AI and Computational ToolsOncology 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 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 bignew ideasto life.

AstraZenecas 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 toultimately eliminatecancer 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 areseekinga highly motivated independent collaborative Senior Scientist to join our Immune Cell Engagers Discovery group in Cambridge UK. This role sits at the intersection ofapplied 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 strongprogrammingand data engineering skills with immunology domainexpertiseto 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 pipelinesvisualisationapps agentic AI solutions and LLM-integrated tools that accelerate experimental decision-making and reduce manual analytical burden.

• Build andmaintaindata infrastructure tocentralisestandardiseand quality control experimental data from functional cell biology assays and multi-omicplatforms design and implement LIMS schemas electronic lab notebook (ELN) workflows and structured databases to ensure data is FAIRreproducibleand 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.

• Mentor and train colleagues in computational methods AI tool use and reproducible data practices.

• Interface with Data Science R&D IT and external platform teams to co-develop scalable solutions contribute to sharedinfrastructureand 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-omicintegration.

• Contribute to the generation understanding and assessment of biological datasets related to functional cell biology assays and multi-omicdata to generate insights relevant to drug development in the Immune Cell Engagers Discovery group.

• Stay up to date with advances in computational biology and AI (methods tools and best practices); proactively evaluate and adopt fit-for-purpose approaches to enhance discovery workflows.

• Prepare and deliver presentations within the Immune Cell Engagers Discovery group and across other functions.

• Ensure compliance with internal standards and external regulations;maintainaccuratetimelyrecords in the ELN.

Essential Requirements

• Proven experience building data infrastructure in a research setting including designing LIMS schemas or ELN workflow building structuredatabasesand developing reproducible data pipelines with automated validation and QC.

• 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.

• Strongproficiencyin Python and/or R and large-scale data management.

• Strong immunology and/or immuno-oncology domainexpertise a working understanding of immune cell biology T cellfunctionand the tumour microenvironment sufficient to independently interpret experimental data and contribute meaningfully to biological discussions.

• 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.

• Strong interpersonal and collaboration skills witha track recordof working effectively across wet-lab and dry-lab teams in a matrixed environment.

• Proventrack recordof scientific accomplishments (e.g. publications/patents).

• Experience preparing written scientific reports and delivering oral presentations

Desirable Skills

• PhD in relevant disciplines or equivalent experience (e.g.Bioinformatics Systems Biology Computational Biology Applied Mathematics Statistics Data Science Computer Science).

• Experience with advanced deep learning model families (graph neural networks transformers probabilistic models) applied to biological data.

• Experience with open data platforms such as Domino/QuartzBio.

• Expertisein T-cell engagers cytokines bispecific moleculestumourmicroenvironmentand/or myeloid biology.

• Experience working with translational datasets.

• Experience in an industry drug discovery setting with knowledge of discovery-stage decision-making.

What You Will Gain

You willoperateat thecutting edgeof oncology discoverycombining AI and data engineeringwithdeep 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 whats next

Are you already imagining yourself joining our team Good because we cant wait to hear from you!

Where can I find out more

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  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.