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

Overview

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), the 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, you will develop and benchmark adaptive multimodal learning models for cancer risk prediction, equipping them with robust domain adaptation capabilities to ensure accuracy across diverse populations and healthcare settings. You will combine multimodal data and domain knowledge to enable interpretable predictions and provide deeper insights into decision-making. Utilising best-practice software engineering, you will build open-source, FAIR-compliant software that is transparent and accessible, while collaborating nationally to shape an open research infrastructure for cancer.

A CV and cover letter are required with your application. Your cover letter must include a link to a representative piece of your writing, a link to a code sample (such as Git Hub or a downloadable zip), and a short description of a past collaboration experience.

• Develop findable, accessible, interoperable, and reusable (FAIR) multimodal AI software, tools, and workflows to support multiple interdisciplinary cancer risk prediction projects across CD3 driver programmes and institutions.
• Build, deploy, and maintain multimodal AI prototypes and models using frameworks such as PyTorch, ensuring reproducibility and robustness.
• Build, maintain and enhance multimodal cancer risk prediction infrastructure, including open-source repositories, documentation platforms, and benchmarking leaderboards on mainstream platforms such as Git Hub or Hugging Face.
• Work closely with other CD3 teams to advise on multimodal AI approaches, data integration, and evaluation protocols, ensuring alignment with open research principles and a deployment-centric focus.
• Contribute to the implementation of baseline multimodal AI models and evaluation protocols for multimodal cancer risk prediction benchmarks.
• Collaborate with other CD3 teams to gather requirements, address technical challenges, and ensure practical, real-world relevance of outputs.
• Disseminate research outcomes through multiple channels, including software packaging and release, technical documentation, contributions to academic papers, conference presentations, tutorials, and other training materials.
• As a member of staff, make ethical decisions in your role and embed the University's sustainability strategy into your work wherever possible.
• Contribute to equality, diversity and inclusion through fostering an inclusive culture in CD3 and participating in initiatives and activities to enable this.
• Carry out other duties commensurate with the grade and remit of the post.

In addition, Senior AI Research Engineers (Grade
7) will:

• Design multimodal learning software architecture and prototypes.
• Lead the writing of high-quality papers/reports on multimodal AI for cancer risk prediction and other ways of disseminating research outcomes.
• Lead multimodal AI training and interactions with collaborators and partners.
• Organise project meetings with stakeholders and manage follow-up actions.

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply. Please…