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 GitHub or a downloadable zip), and a short description of a past collaboration experience.
Main duties and responsibilities
- 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 GitHub 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.
Person Specification
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 ensure that you reference the application criteria in the application statement when you apply.
Bachelor’s or master’s degree in computer science, engineering, applied mathematics, data science or a related area (or equivalent experience).
Ability to work effectively as part of a team, with good time and project management skills.
In-depth knowledge and solid practical skills in AI, machine learning, and data analysis.
Ability to carry out evidence-based assessment and decision-making, and to develop end-user-targeted software and disseminate research outcomes.
Effective communication skills, both written and verbal, including report and paper writing.
Ability to work in an interdisciplinary environment and collaborate with researchers from subject areas other than your own to specify, develop, improve, and deliver research software.
Familiarity with reproducible software development using best practices in software engineering, including testing, documentation, and version control.
Experience with collaborative software development on GitHub or equivalent platforms.
Desirable (G6)
Essential (G7)
Experience with healthcare and biomedical research, and PyTorch and related machine learning frameworks.
Desirable (G6)
Essential (G7)
Further Information
Grade 6 (AI Research Engineer) / Grade 7 (Senior AI Research Engineer)
AI Research Engineer: £32,080 - £36,636 per annum
Senior AI Research Engineer: £38,784 - £41,064 per annum
Until 31st March 2027, with the potential for the position to be extended subject to receiving further funding.
Head of AI Research Engineering
If you do not currently hold the right to work in the UK, you can find more information here to help determine your visa eligibility. Additional guidance is also available on the UK Visa & Immigration website.
For informal enquiries about this job, contact Professor Haiping Lu, Head of AI Research Engineering, at
[email protected]Next steps in the recruitment process
It is anticipated that the selection process will take place in the week commencing 31st August 2026. This will consist of a Python coding test, a short presentation of a research paper, and an interview. We plan to let candidates know if they have progressed to the selection stage in the week commencing 24th August 2026. If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process, you can contact
[email protected]Our vision and strategic plan
We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision ().
What we offer
- A minimum of 38 days' annual leave (41 for Senior AI Research Engineer), including bank holiday and closure days (pro rata) with the ability to purchase more.
- Flexible working opportunities, including hybrid working for some roles.
- Generous pension scheme.
- A wide range of discounts and rewards on shopping, eating out and travel.
- A variety of staff networks, providing opportunities for social interaction, peer support and personal development (for example, Race Equality, LGBT+, Women’s and Parent’s networks).
- Recognition Awards to reward staff who go above and beyond in their role.
- A commitment to your development access to learning and mentoring schemes.
- A range of generous family-friendly policies
- paid time off for parenting and caring emergencies
- support for those going through the menopause
- paid time off and support for fertility treatment
- and more
We are a Disability Confident Leader (opens in a new window). If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.
