Research Associate - Department of Cancer and Genomic Sciences - 107471 - Grade 6 in Birmingham

Research Associate - Department of Cancer and Genomic Sciences - 107471 - Grade 6 in Birmingham

Birmingham Full-Time 33002 - 35608 € / year (est.) Home office (partial)
The University of Birmingham

At a Glance

  • Tasks: Support groundbreaking research in diabetes using AI and real-world data.
  • Company: University of Birmingham, a leader in health data science and innovation.
  • Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
  • Other info: Join a diverse team committed to sustainability and inclusivity.
  • Why this job: Make a real impact on healthcare by validating AI models for diabetes treatment.
  • Qualifications: Degree in Health Data Science or related field; experience with data analysis tools.

The predicted salary is between 33002 - 35608 € per year.

This post supports the NIHR BRC-funded study TRANsCEnD-CPRD: Validation of a Foundation Model for diabetes and multimorbidity (Diabetes2Vec) using real-world primary care data, which focuses on the validation and fairness evaluation of a transformer-based AI model for predicting individual diabetes progression and treatment outcomes in UK primary care populations.

The post holder will be based within the Department of Cancer and Genomic Sciences (CGS) and will join the Centre for Health Data Science, working under the supervision of Dr Andreas Karwath and in close collaboration with the co-investigators, Professor Nicola Adderley (BRC Data Theme Deputy Lead) and Dr Chris Sainsbury, as well as the project collaborator, Dr Feng Dong (University of Strathclyde). The role will provide technical and analytical support for the adaptation of existing model code to the CPRD environment, the validation of the Diabetes2Vec model on nationally representative primary care data, and the systematic audit of model performance across ethnic minority groups. The post will focus primarily on computational analysis, data transformation, and equity evaluation within a trusted research environment.

The TRANsCEnD-CPRD team are seeking an individual with a degree or equivalent in Health Data Science, Computer Science, Artificial Intelligence, or a closely related discipline relevant to clinical predictive modelling and fairness in machine learning, who has practical experience in its application using established tools (for example, NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow) and procedures. Experience working with electronic health records or primary care data, and in preparing, structuring, and analysing large-scale longitudinal datasets, is desirable.

The anticipated start date is June 2026. The post will be offered on a hybrid working basis, with an expectation of at least three days per week in the office.

Role Summary

The Research Associate role is a fixed-term post working within the defined NIHR BRC-funded research project focused on the validation of a transformer-based foundation model (Diabetes2Vec) for diabetes and multimorbidity using real-world primary care data from CPRD Aurum, linked to Hospital Episode Statistics Admitted Patient Care (HES APC). You will apply skills in health data science, sequence modelling, and clinical AI evaluation to support data transformation, model validation, and fairness audit activities within a trusted research environment (DEXTER). You will also carry out predefined model performance analyses and equity assessments across defined population subgroups, under the direction of senior researchers.

The Research Associate will be expected to prepare, structure, and quality-check CPRD primary care data, including the generation of clinical event tokens and cohort definitions aligned with established project protocols and BRC standards. You will also be expected to provide technical and analytical support within a multidisciplinary team to support agreed project objectives, and contribute to the reporting of research outputs, including reports, conference presentations, and publications. As part of the role, you will use and maintain computational pipelines, tokenisation workflows, and version-controlled codebases to support reproducible analyses, and will contribute to the preparation of preliminary data supporting a subsequent large-scale NIHR or MRC grant submission.

The University of Birmingham is committed to creating a more sustainable university and world. The Department of Cancer and Genomic Sciences and the Centre for Health Data Science are dedicated to minimising our environmental impact, promoting social responsibility, and fostering a diverse and inclusive workplace. We are working towards environmentally responsible practices and team members are expected to contribute towards achieving these goals.

Main Duties

  • Collect research data; this may be through a variety of research methods, including but not limited to Dexter, CPRD, scientific experimentation, literature reviews, and research interviews.
  • Analyse research data as directed.
  • Develop or adapt techniques, models and methods.
  • Present research outputs, including drafting academic publications or parts thereof, for example at seminars and as posters.
  • Provide guidance as required to support staff and any students who may be assisting with research.
  • Deal with problems that may affect the achievement of research objectives and deadlines.
  • Carry out administrative tasks related directly to the delivery of the research.
  • Promote equality and value diversity acting as a role model and fostering an inclusive working culture.

Person Specification

  • Degree or equivalent in relevant subject area.
  • Practical experience of applying the relevant skills and techniques.
  • Ability to analyse information and communicate effectively in written and verbal form within a multi-disciplinary team.
  • Ability to access and organise resources successfully, with the ability to plan and prioritise tasks to meet agreed deadlines.
  • Knowledge of the protected characteristics of the Equality Act 2010, and how to actively ensure in day-to-day activity in own area that those with protected characteristics are treated equally and fairly.

Informal enquiries to Andreas Karwath, email: a.karwath@bham.ac.uk

Use of AI in applications: We want to understand your genuine interest in the role and for the written elements of your application to accurately reflect your own communication style. Applications that rely too heavily on AI tools can appear generic and lack the detail we need to assess your skills and experience. Such applications will unlikely be progressed to interview.

We believe there is no such thing as a 'typical' member of University of Birmingham staff and that diversity in its many forms is a strength that underpins the exchange of ideas, innovation and debate at the heart of University life. We are committed to proactively addressing the barriers experienced by some groups in our community and are proud to hold Athena SWAN, Race Equality Charter and Disability Confident accreditations. We have an Equality Diversity and Inclusion Centre that focuses on continuously improving the University as a fair and inclusive place to work where everyone has the opportunity to succeed. We are also committed to sustainability, which is a key part of our strategy. You can find out more about our work to create a fairer university for everyone on our website.

Research Associate - Department of Cancer and Genomic Sciences - 107471 - Grade 6 in Birmingham employer: The University of Birmingham

The University of Birmingham offers an exceptional work environment for the Research Associate role within the Department of Cancer and Genomic Sciences, fostering a culture of inclusivity, collaboration, and innovation. Employees benefit from a commitment to professional development, hybrid working arrangements, and the opportunity to contribute to impactful research that addresses real-world health challenges. With a focus on sustainability and social responsibility, the university is dedicated to creating a diverse workplace where every team member can thrive and make a meaningful difference.

The University of Birmingham

Contact Detail:

The University of Birmingham Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Associate - Department of Cancer and Genomic Sciences - 107471 - Grade 6 in Birmingham

Tip Number 1

Network like a pro! Reach out to current or former employees at the University of Birmingham, especially in the Department of Cancer and Genomic Sciences. A friendly chat can give you insider info and maybe even a referral!

Tip Number 2

Prepare for your interview by brushing up on your technical skills. Make sure you can confidently discuss tools like NumPy, Pandas, and PyTorch. We want to see your passion for health data science shine through!

Tip Number 3

Showcase your projects! If you've worked on relevant research or have experience with electronic health records, be ready to talk about it. Real-world examples can set you apart from the crowd.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to engage with us directly.

We think you need these skills to ace Research Associate - Department of Cancer and Genomic Sciences - 107471 - Grade 6 in Birmingham

Health Data Science
Computer Science
Artificial Intelligence
Clinical Predictive Modelling
Fairness in Machine Learning
Data Transformation
Model Validation

Some tips for your application 🫡

Be Yourself:When writing your application, let your personality shine through! We want to see your genuine interest in the role, so avoid using AI tools too heavily. Make sure your communication style reflects who you are.

Tailor Your Application:Make sure to customise your application for this specific role. Highlight your relevant skills and experiences that align with the job description, especially in health data science and AI. Show us why you're the perfect fit!

Showcase Your Experience:Don’t just list your qualifications; provide examples of how you've applied your skills in real-world situations. Whether it’s working with primary care data or using tools like NumPy and TensorFlow, we want to hear about it!

Check Your Work:Before hitting send, take a moment to proofread your application. Spelling and grammar mistakes can distract from your message. A polished application shows attention to detail, which is crucial for this role!

How to prepare for a job interview at The University of Birmingham

Know Your Stuff

Make sure you’re well-versed in the specifics of the role, especially around health data science and AI. Brush up on tools like NumPy, Pandas, and PyTorch, as they’ll likely come up in conversation. Being able to discuss your practical experience with these tools will show you’re ready for the job.

Show Your Passion for Research

Demonstrate your genuine interest in the research area, particularly the validation of AI models in healthcare. Be prepared to discuss why this project excites you and how your background aligns with their goals. This will help you stand out as a candidate who’s not just looking for any job, but is truly invested in this specific role.

Prepare for Team Dynamics

Since you’ll be working in a multidisciplinary team, think about examples from your past experiences where you’ve successfully collaborated with others. Highlight your communication skills and how you’ve contributed to achieving common goals. This will reassure them that you can fit into their team culture.

Understand Their Values

Familiarise yourself with the University of Birmingham's commitment to diversity, sustainability, and inclusion. Be ready to discuss how you can contribute to these values in your role. Showing that you align with their mission will make a positive impression and demonstrate that you’re a good cultural fit.