At a Glance
- Tasks: Develop innovative AI models for cancer risk prediction and collaborate on groundbreaking research.
- Company: Join the University of Sheffield's Centre for Machine Intelligence, a leader in transformative research.
- Benefits: Enjoy flexible working, generous leave, and a supportive environment for personal development.
- Other info: Be part of a diverse community committed to equality and inclusion.
- Why this job: Make a real impact in cancer research while advancing your skills in AI technology.
- Qualifications: Experience in software development and a passion for interdisciplinary collaboration.
The predicted salary is between 32080 - 36636 £ per year.
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.
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.
- 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.
Further Information:
- Grade: Grade 6 (AI Research Engineer) / Grade 7 (Senior AI Research Engineer)
- Salary: AI Research Engineer: £32,080 - £36,636 per annum; Senior AI Research Engineer: £38,784 - £41,064 per annum
- Work arrangement: Full-time
- Duration: Until 31st March 2027, with the potential for the position to be extended subject to receiving further funding.
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.
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.
- 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.
AI Research Engineer / Senior AI Research Engineer in Cancer Data Driven Detection in Sheffield employer: Diversity Dashboard
Diversity Dashboard is an exceptional employer that prioritises inclusivity and professional growth, making it an ideal place for those passionate about tackling inequality and poverty. With a flexible working environment in the vibrant city of Edinburgh, employees benefit from a supportive work culture that encourages collaboration and continuous learning, ensuring that every team member can thrive in their role while making a meaningful impact in the community.
StudySmarter Expert Advice🤫
We think this is how you could land AI Research Engineer / Senior AI Research Engineer in Cancer Data Driven Detection in Sheffield
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Diversity Dashboard!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Research Engineer / Senior AI Research Engineer in Cancer Data Driven Detection at Diversity Dashboard.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Diversity Dashboard.
✨Apply Directly through Our Website
When you find a suitable opening like AI Research Engineer / Senior AI Research Engineer in Cancer Data Driven Detection at Diversity Dashboard, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace AI Research Engineer / Senior AI Research Engineer in Cancer Data Driven Detection in Sheffield
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Diversity Dashboard, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Diversity Dashboard. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Diversity Dashboard
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Diversity Dashboard!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
