This year, the NortHFutures Digital Health Hub has helped broaden and deepen the pool of talent in the health data research sector by sponsoring seven places on Health Data Research UK’s pioneering Black Internship Programme (BIP).
The BIP, organised by Health Data Research UK (HDR UK), fosters a more diverse and inclusive pipeline of health data scientists – critically, one that’s more representative of British society.
It matches Black students and recent graduates, who want to develop their health data science skills, with hosts from the NHS, social care, the third sector, social enterprise, business and elsewhere.
They spend eight weeks over the summer carrying out a paid, practical, real-world project with direct benefits for health and care.
The NortHFutures cohort illustrates not only the breadth of the paid internships, but also the value for the host organisations.
Below we’ve summarised the 2025 projects, with comments from hosts and participants.
Creating a Local Food Price Index - Citizens Advice Gateshead
Intern: Somto Uche
Host: Neil Gow
Somto has been developing a model to create an ongoing food price index for Gateshead, focusing on the consumption patterns of low-income households, and contrasting the experience of urban eastern Gateshead, with rural western Gateshead.
Neil said: “When we talk about a ‘cost of living crisis’ we sometimes miss the detail about the real impact for low-income households when it comes to food.
“This project will create a rolling metric with which we can measure the actual changes across Gateshead and consequently inform policy makers about the hyperlocal impact of regional and national changes.
“A project like this needs to be based on robust methodology and be designed in such a way that it is easily sustainable beyond the term of the internship.”
Measuring the Metabolic Rate of Cancer Cells - Teesside University Intern: Brandon Coke
Supervisor: Professor Annalisa Occhipinti
The project involves developing a web application that integrates AI to investigate metabolic changes in cancer cells versus normal cells. It involves working with medical imaging, genomic data, and patient records to create a functional AI-based platform for researchers and clinicians.
Brandon said: “I have built a pipeline to convert the RNA-seq reads into metabolic flux matrices. Additionally, I have produced a prototype dashboard using these flux matrices.
“To overcome the numerous challenges I have encountered, I have taken time to refine and learn new techniques and packages in Python as well as leverage the expertise of Professor Occhipinti’s lab.”
Prof. Occhipinti, commented that hosting this internship has been a valuable opportunity for both our AI research group and Teesside University.
She said: “It's great to support and mentor emerging talents while also advancing our work and contributing to AI-driven health applications.”
Fair Data Visualisation in Healthcare - Newcastle University
Intern: Adedayo Omoniyi
Supervisor: Dr Vlad Gonzales
Adedayo’s internship concentrated on fair data visualisation for healthcare. Specifically, plots that represent high-dimensional data, such as records containing lots of demographic data, as well as symptoms and test results.
To visualise these datasets, it is necessary to apply dimensionality reduction (DR) to the data, so it can be plotted. Algorithms exist to do this but can be poor in areas such as the representation of minority groups. Fair versions of these algorithms are essential.
Adedayo said: “The objective is to assess how DR techniques influence downstream machine learning (ML) tasks, such as classification and clustering, while examining their ability to preserve fairness across sensitive demographic subgroups, including ethnicity, age, marital status, and gender.
“By integrating quantitative fairness metrics with visual analytics, the project aims to develop actionable insights and practical guidelines for the responsible application of dimensionality reduction in clinical data science workflows.”
Dr Gonzales described it as “a privilege” to host BIP interns. He said: “BIP tackles real-life ethical concerns on how healthcare data is managed and represented, and supports the democratisation of access to academia and research
“The programme provides interns with experiences that may lead them to pursue a PhD in data sciences in the near future.
“My experience with Adedayo has been excellent, as he is very motivated and hard-working.”
Lymphoedema Quality of Life Measure - St Oswald’s Hospice
Intern: Angel Obinna-Uzoh
Supervisor: Simon Gordon
This internship involved working on the Lymphoedema Quality of Life Measure Project which aims to develop a structured, data-driven way to measure and track how the hospice’s lymphoedema service impacts patients’ quality of life over time.
Angel explained that the emphasis is on transforming qualitative patient-reported data into quantitative metrics that can be used consistently.
She said: “I’ve been reviewing existing data, identifying common themes in patient responses, and building a scoring system that reflects the severity of reported issues.
“I’m also testing this framework with real patient data to ensure it is practical and meaningful for clinical teams. The outcome will be a robust tool that supports long-term service evaluation and improvement.”
According to Simon, the work done by Angel is invaluable and, with the charitable sector struggling for funding, it is hugely important to have access to sponsored talent of this kind.
He said: “Angel’s work with our Lymphoedema Service brings together data science and patient care in a truly meaningful way.
“By engaging directly with patients and learning from our clinical team, Angel is helping shape a set of data points that are not only reliable, but genuinely reflective of what matters most to the people we support. While data is at the heart of this work, its focus remains deeply human – centred on wellbeing, lived experience, and the quality of care we deliver.
“In a climate where funding for the charity sector is increasingly competitive, this kind of insight is invaluable. It strengthens our ability to advocate for the resources we need, so we can continue to offer the high-quality, person-centred care our community expects.
“We simply couldn’t do this without the support of NortHFutures – or without brilliant people like Angel.”
Predicting Patient Attendance - Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust (CNTW)
Intern: Golden Osabuohien
Supervisor: Arne Walters
Failure to attend appointments has serious consequences for the health service. This project aims to provide insights on an issue that costs time, money and may have an impact on people’s health and wellbeing.
Golden said: “My project focuses on those who do not attend (DNAs) [health service appointments] by analysing factors like ethnicity and consultation modes (remote vs. in person).
“I’ve been exploring how we can better support patients and reduce missed appointments. By using predictive modelling techniques, I aim to help healthcare providers improve patient engagement and address challenges related to digital exclusion.”
Motion Reconstruction for Parkinson’s Patients Using Sparse Wearable Sensors - Northumbria University
Intern: Valerie Fiamavle
Supervisor: Bing Zhai
This project aims to explore how a minimal sensor configuration can be used to track the progress of Parkinson’s disease. The idea is to capture and reconstruct full-body motion, providing valuable insights for clinical assessments, rehabilitation, and assistive technologies.
Valerie sees it as an important opportunity to expand her skills. She said: “By the end of my internship, I hope to gain a solid understanding of Python and to further sharpen my research skills.
“I have been actively self-teaching myself Python using online courses and I have been inquisitive in the project to aid the development of my research skills.”
A Privacy-Preserving AI System - Newcastle University
Intern: Folu Akintola
Supervisor: Dr Dev Jha
Folu has been working on a project titled Adaptive Federated Healthcare System with Model Compression and Lifelong Learning, which is designing an adaptive, privacy-preserving AI system that includes model compression and lifelong learning.
Folu said: “The aim is to explore how these techniques can be used to develop more efficient and equitable healthcare models, especially in environments where data privacy and resource constraints are significant. It's been a valuable learning experience, combining technical research with real-world health challenges.”
Hosting an intern through the BIP reflected the university’s commitment to diversity, inclusion, and supporting underrepresented talent in STEM.
Dr Jha said: “By involving the intern in cutting-edge research on Adaptive Federated Healthcare Systems, we provided an opportunity to contribute to a project with real-world impact on privacy-preserving and scalable healthcare solutions.
“This collaboration not only enriches our research but also reinforces our belief that diverse perspectives drive innovation and meaningful progress.”
For more about BIP click here.