Our Summer Internship Programme is back for another year, and we are delighted to welcome this year’s cohort of 17 interns to our multidisciplinary teams across Population Data Science at Swansea University.
Each year, our Summer Internship Programme brings together students from a range of disciplines, including data science, research, and software development, providing them with the opportunity to gain valuable hands-on experience in a real-world research environment. Working alongside our award-winning teams, interns contribute to meaningful projects using anonymised data and cutting-edge technical platforms, while developing the skills and experience to support their future careers.
Throughout this four-part blog series, we’ll introduce this year’s interns and share insights into their projects, interests, and aspirations for the future.
Amarachi Jovita Njoku
Where and what were you studying before you started your internship?
Before starting this internship, I was (and still am) studying for an MSc in Bioinformatics with Teesside University in England.
What attracted you to apply to the Population Data Science internship programme?
I was keen to gain practical experience and skills working in a real research environment. The internship’s focus on real, large-scale health data drew me to apply. It was an opportunity to contribute meaningfully to health research while learning from experienced professionals.
Could you tell us a little about the project you will be/are working on?
My project with the Dementia’s Platform UK (DPUK) team on Genomics Tool Development is focused on standardising omics metadata across DPUK and preparing it for integration into a Gen3 data platform. It involves creating a common metadata framework that maps DPUK metadata to formats compatible with Gen3. The overall aim is to make these datasets easier to discover and manage for future research while supporting fair data practices.
What do you hope to learn, achieve, or contribute during your time with us?
I hope to gain hands-on experience in building a research data infrastructure, from inventory and metadata standardisation to schema validation and integration design. I hope to deepen my technical and professional skills and become more confident in using tools such as Python, Git, and Gen3 in a real research environment. As for my contribution, I want to leave behind something that is genuinely useful, a well- documented crosswalk with a gap report that would show what exists, what is missing and what needs to happen next. If I can achieve these, I would consider the internship a success.
Do you have a career in mind at the moment, and how do you hope the internship will help you towards that goal?
At the moment, I am aiming for a career as a Bioinformatician/ Data Engineer/ Data Analyst with particular interest in data management and infrastructure (building systems that make large biological datasets findable and reusable). This internship is directly toward that goal. The work I’m doing, designing metadata frameworks, data dictionaries, etc reinforce the key responsibilities of a Bioinformatician in a data-focused role.
Aparna Maruthiyodan Puthanveedu
Where and what were you studying before you started your internship?
I was doing my MSc in Big Data Science at Queen Mary University London.
What attracted you to apply to the Population Data Science internship programme?
I first came across the Population Data Science internship programme in 2025 and applied because I was strongly interested in the opportunity to use data science to support population health research and decision-making. Although I was unsuccessful that year, my interest in the programme remained, and I continued to keep an eye out for future opportunities. What attracted me most is the opportunity to apply my academic background in Data Science to real-world health and population contexts. My master’s degree has helped me develop strong analytical, problem-solving, and technical skills, while my recent experience as an NHS Administrator has given me valuable insight into healthcare systems, patient data, and the importance of accurate information in improving services. This programme feels like an excellent opportunity to bring together my data science skills and healthcare experience. I am keen to contribute my knowledge, learn from experienced professionals, and further develop my expertise in population data science.
Could you tell us a little about the project you will be/are working on?
The project I will be working on will use the SAIL Databank to explore recent trends in influenza and COVID-19 vaccine uptake across Wales. With growing concern that vaccination rates may be declining, the project will examine how uptake has changed over time and how it varies across demographic and clinical groups. I will analyse patterns in vaccine uptake across factors such as age, sex, geographic area, and relevant health conditions. This will help identify whether certain groups are less likely to receive vaccines and whether any inequalities in uptake are emerging. By building a clearer picture of these trends, I hope the project will contribute to a better understanding of vaccine uptake in Wales and help inform future public health strategies.
What do you hope to learn, achieve, or contribute during your time with us?
During my time with the Population Data Science internship programme, I hope to further develop my practical data science skills and gain a deeper understanding of how population-level data can be used to improve health outcomes, services, and decision-making. I am particularly keen to learn how data is collected, managed, analysed, and interpreted within a healthcare and public health setting. I hope to achieve greater confidence in applying my technical skills to real-world projects, including data analysis, problem-solving, and communicating findings clearly to different audiences. I would also like to learn from experienced professionals and better understand the role of data science in supporting evidence-based healthcare. I believe I can contribute my academic knowledge from my master’s degree in data science, along with my recent experience as an NHS Administrator. My NHS experience has helped me understand the importance of accurate data, confidentiality, organisation, and patient-focused services. I am motivated to contribute positively to the team, support meaningful projects, and continue developing as a future data professional in the health sector.
Do you have a career in mind at the moment, and how do you hope the internship will help you towards that goal?
At the moment, I am interested in building a career as a Health Data Analyst. My master’s degree in data science has given me a strong foundation in data analysis, problem-solving, and technical skills, while my recent experience as an NHS Administrator has helped me understand the importance of accurate data, confidentiality, and efficient healthcare systems. In the future, I would like to work in a role where I can use health data to identify patterns, support evidence-based decision-making, and contribute to improving patient care and population health outcomes. I am also interested in how data can be used to understand health inequalities and improve healthcare services for different communities. I hope this internship will help me move towards this goal by providing practical experience applying data science to real-world population health projects. It would allow me to learn from experienced professionals, strengthen my technical and communication skills, and gain a clearer understanding of how health data is used within research, public health, and healthcare decision-making.
Aylin Naebzadeh
Where and what were you studying before you started your internship?
Currently, I’m an MSc student in AI and Data Science at the University of Hull in East Yorkshire. My BSc was in Computer Engineering at Iran University of Science and Technology.
What attracted you to apply to the Population Data Science internship programme?
Two things I liked the most. Firstly, equal opportunity for all students. It was not required to be a student at Swansea. Secondly, diversity among project topics, ranging from data analysis and literature review to AI and software engineering.
Could you tell us a little about the project you will be/are working on?
I’m going to work with SeRP on an impact-tracking project with some integration with large language models to make it automated.
What do you hope to learn, achieve, or contribute during your time with us?
Gain hands-on experience and play a positive role (although it’s very short).
Do you have a career in mind at the moment, and how do you hope the internship will help you towards that goal?
The thing I like most is working at the intersection of industry and academia. I’ve heard about KTP roles. Maybe in future I could secure one.
Cerith Halfpenny
Where and what were you studying before you started your internship?
I graduated from Cardiff University in 2019 with a degree in Medical Pharmacology and am currently studying for an MSc in Applied Data Science at Swansea University. Between the two, I spent over five years working in clinical trials across both commercial and academic settings in functions such as pharmacovigilance, clinical data management and trial governance.
What attracted you to apply to the Population Data Science internship programme?
The range of fascinating projects available aligned perfectly with my goal of moving into administrative and health data science by combining my professional experience with my MSc. The opportunity to work within an established research team and contribute to real-world health research and outcomes made this internship stand out from others.
Could you tell us a little about the project you will be/are working on?
I am working on the MAGENTA project, which is investigating the impact of extreme heat on pregnancy outcomes. Specifically, my work investigates how socioeconomic and environmental factors (including temperature, humidity, and air quality) are associated with preterm birth rates across Wales. I will be using Bayesian spatial modelling to identify geographical variation in risk. The aim is to provide evidence that policymakers can use to improve birth outcomes.
What do you hope to learn, achieve, or contribute during your time with us?
I am motivated to develop practical skills by combining my clinical research experience with the data science knowledge I am gaining through my MSc, to pursue a career in health data science. I also hope to make a meaningful contribution to the wider project and its goal of improving maternal and neonatal health while reducing health inequalities across Wales.
Do you have a career in mind at the moment, and how do you hope the internship will help you towards that goal?
My goal is to build a research career in this field. This internship will give me invaluable hands-on experience with real-world data and the opportunity to develop practical skills that are difficult to acquire through postgraduate study alone. I hope this experience will make me a much stronger candidate for future roles.
For the latest updates on our Intern Programme, visit https://popdatasci.swan.ac.uk/about-us/summer-internship-programme/