The Widening Participation (WP) Research Summer Internships provide undergraduates with hands-on experience of research during the summer holidays, with the aim of encouraging a career in research. Interns gain professional experience and knowledge through a funded placement in their chosen subject. This also supports application for postgraduate study and other research jobs.
This year, the JGI was very pleased to support four internships through the WP scheme. Each of the interns has provided valuable support to an array of diverse and interesting projects related to their fields of interest. We are delighted by the feedback that we have received from their project supervisors and look forward to watching their future progress. Read on for more information on their projects and their experience.
Frihah Farooq
My name is Frihah, and I’m a third year undergraduate studying Mathematics here at the University of Bristol. My academic interests centre around applied data science and machine learning, and this summer I worked on a project involving the General Practice Workforce dataset published by NHS Digital. My focus was on building tools that could bring accessibility to data that is often scattered and difficult to navigate.
The aim of the project was to automate the downloading and linkage of open-access datasets, specifically in the context of healthcare services. Many of these records are stored in files with inconsistent formats and structures, often requiring manual effort to piece together a consistent narrative. I developed a codebase in R that could search for the appropriate files, extract the relevant information, and construct a complete dataset that can be used for longitudinal analysis without the need for repeated intervention. While the code was built around the workforce dataset, the methodology generalises well to other datasets published by NHS Digital.
One observation from the final merged dataset was the trend of decreasing row counts, likely due to restructuring, alongside an increase in the number of recorded variables, a sign that data collection has grown more sophisticated in recent years. This experience strengthened my foundation in data automation and my ability to work with evolving and imperfect data; skills I know will benefit me as I move further into research.
If you’d like to get in touch, you can reach me at cc22019@bristol.ac.uk
Grace Gilman
Hello, my name is Grace Gilman and I am starting my third year studying Computer Science with Artificial Intelligence at the University of Bath. I am hoping to go into academia in the future and pursue computing research specifically with medical applications. You can contact me at gcag20@bath.ac.uk.
Over the six weeks I have been participating in a research internship here at the University of Bristol, supported by the Jean Golding Institute. I have been working on a data science project called ‘Using AI to Study Gender in Children’s Books’, for the team Fair Tales, supervised by Chris McWilliams. During my internship I experimented with image analysis using ChatGPT and Vertex AIi, for future integration into the Data Entry app that Fair Tales is producing to semi-automate character and transcript input. I have also been contributing to the database architecture and search and filtering options for users to interact with the database. Some of my work has been analysing the corpus of children’s books using SQL, one pattern I found was that the difference between mother and father characters(1:0.75) is even more pronounced for grandmothers and grandfathers(1:0.5).
During my time at this internship, I have become much more confident in my abilities to work on a project as well as code that will be used in a research setting. I have learnt more of how research is conducted and what skills are needed for this, and become more sure of an academic future.
Imogen Joseph
I am currently studying a Neuroscience MSci with a Year in Industry at the University of Bristol. I’m going into my final year, having just completed a placement year in Southampton General Hospital undertaking clinical research in neonatal respiratory physiology. I’m particularly interested in a career in academia and more specifically looking at molecular mechanisms behind disease for drug discovery.
This summer, I helped in the development of an R package, ‘midoc’ (Multiple Imputation DOCtor, found on CRAN), designed to guide researchers in analysis with missing data under my supervisor Elinor Curnow. I created several functions that resulted in the display of a summary table of missing data, alongside optional graphs to visualise the distributions of their missing data. This allows the user to explore what is actually missing, and additionally make inferences on whether missingness is random or related to particular variables.
Before coming into this internship, my R ability was limited to self-teaching via youtube videos. Ample training was provided in this project but more than anything, throwing myself in and actually writing code has been so beneficial to my learning. This knowledge is extremely useful for a career in research – I was even able to apply my acquired skills onto the work carried out in my placement, and used R to analyse the data I gathered.
I am very grateful for this opportunity given to me under the JGI and will take what I’ve learnt with me into whatever I do next!
You can contact Imogen at imogenjoseph26@gmail.com
Sindenyi Bukachi
Using Big Data to Rethink Children’s Rights (bsindenyi@gmail.com)
MSci Psychology and Neuroscience, University of Bristol (Year 3)
Initially, the project was quite open – the only brief was to explore attitudes towards children’s rights using big data. My early research into Reddit threads, news stories and real-world discourse helped narrow our focus to something more urgent and measurable: children’s right to participation, specifically in educational settings as both my supervisors are based in the School of Education. This became the foundation for the rest of the project, and my supervisors later decided to take it forward as a grant proposal.
Over the first few weeks, I learned how to do structured literature reviews using academic databases like ERIC, build Boolean search strings, and track findings across a spreadsheet. I explored how participation is talked about and measured, and the themes I identified – like tokenism, power struggles between adults, and the emotional toll of being “heard” but not actually listened to – became central to our research direction.
In the second half, I moved from qualitative sources to dataset analysis. I used R and RStudio to explore datasets from the UK Data Service. I learned to work with tricky file types (.SAV, .TAB), use new packages, extract variables, visualise trends, and test relationships between predictors — all while thinking critically about how these datasets (often not made for this topic) could reflect participation and children’s agency.
I’ve gained confidence in data science, research strategy, and independent problem-solving – all skills I’ll take forward into my dissertations and future career. I’m so grateful to Dr Katherin Barg, Professor Claire Fox, and the JGI for the support and trust throughout.