AI Research Engineer / Senior AI Research Engineer in Cancer Data Driven Detection


Company:	University of Sheffield
Salary:	Not specified
Hours:	Full-time
Location:	Sheffield, S10 2TN
Job type:	Temporary
Posting date:	24 Jul 2026
Closing date:	23 Aug 2026

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Summary

University of Sheffield

Job Reference Number:

2894

Faculty:

Faculty of Engineering

School:

School of Computer Science

Closing Date:

23rd August 2026

You will join the AI Research Engineering team within the University of Sheffield’s Centre for Machine Intelligence, supporting the Cancer Data Driven Detection (CD3) programme. CD3 is a new, multidisciplinary and multi-institutional strategic national research programme dedicated to using data to transform our understanding of cancer risk and enable early interception of cancers. It represents a major, multi-million-pound flagship investment funded through a strategic programme award by Cancer Research UK, the National Institute for Health and Care Research (NIHR), Engineering and Physical Sciences Research Council (EPSRC), and the Peter Sowerby Foundation; in partnership with Health Data Research UK (HDR UK) and the Economic and Social Research Council’s Administrative Data Research UK programme (ADR UK).

As an AI Research Engineer for CD3, you will develop and benchmark adaptive multimodal learning models for cancer risk prediction. This will include equipping models with robust domain adaptation capabilities to ensure they remain accurate and reliable across diverse populations, healthcare settings, and time periods. It will also involve combining multimodal data and domain knowledge to enable interpretable predictions and provide deeper insights into decision-making processes. You will use best-practice software engineering and open science principles to build open-source software that ensures the tools developed are FAIR-compliant, transparent, and accessible to the broad research community. You will collaborate closely with CD3 members at other institutions and have opportunities to shape a national-scale open research infrastructure for cancer.

A CV and cover letter are required with your application. In your cover letter, please include: 1) a link to a representative piece of your writing, 2) a link to a code sample (for example GitHub or a downloadable zip), and 3) a short description of a collaboration experience.

We are committed to exploring flexible working opportunities which benefit the individual and University.

We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.

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