Oran Timoney

Oran Timoney completed his Nuffield Research Placement at Ulster University in 2018. His project focused on Bio informatics and data analytics. Oran won an award for his work at the BT Young Scientist and Technology Competition. We asked Oran some questions about his time during his placement.

Hi! Tell us a little about yourself

Hello. My name is Oran Timoney from Northern Ireland. I completed a Nuffield Research placement in the summer of 2018.

What attracted you to apply for a Nuffield Research Placement?

As someone interested in Computer Science, there is little to no opportunity to have relevant work experience within my area, either due to a lack of businesses or places available. In our school, we regularly have talks from outside organisations to discuss possible opportunities, jobs or careers for the future. On one occasion, Sentinuscame in to discuss careers in IT and their IT Bursary Placement. I decided to apply for this placement.

As Sentinus also co-ordinates the Nuffield Research Placements in Northern Ireland, It was suggested for me apply for this scheme as well.

How did you apply?

It was pretty easy to fill out the application, the online application system allowed me to choose the subjects I was interested in so that the placement chosen can be relevant to this.

A few weeks later, I was accepted into the Nuffield Placements process, where they would pair you up with a suitable organisation for you to attend under the placement for 2-6 weeks.

What was your placement and what did it involve?

I was put on a placement with the NI Centre for Stratified Medicine at Ulster University, under my supervisor Dr Steven Watterson. He was amazing to work with and was always there to point me in the right direction for the aim of my project, and the work created from this to help further research into this area.

I was tasked to analyse the factors which would affect people with low, medium and very high risk of Cardiovascular Disease and the correlation between such factors. I used a program which is called “Orange” to look at visual distributions and other analyses to determine the most effective factors within my dataset. I learned how to research quickly and effectively for correlations between the data I had, and its connotations concerning Cardiovascular Disease. This, in turn, would streamline my dataset and make sure that everything would be relative to my work.

Utilising my dataset, the factors left would then be used to categorise patients using machine learning models. Machine learning models are mathematical algorithms designed to find the threshold between low risk, medium risk and very high-risk patients in my case. I had 200 patients in my final version of the data which would be a problem when my goal is to find a way to classify the population. I researched methods to use with different machine learning model implementations to make the predictions to be based on the general population, rather than 200 people. I also had to make sure that the model was accurate (75% or higher) without sacrificing the credibility of the model or methods used.

After getting a general basis for accurate prediction of Cardiovascular Disease patients, I then implemented a script made within the Python programming language to automatically classify database files with me. This script would also generate a report giving me accuracy information, but also the parameters used in each circumstance to essentially have a repeatable test. If you cannot repeat the test to some degree of accuracy, then it would be useless in any real-world application.

What did you learn over the course of the placement?

The main thing I learned throughout my six-week placement is how to work completely independently of others, and how to plan out my work, with future goals in mind.

I spent significant time making sure that all of the methods carried out in the report were robust, and that I took a lot of screen captures of what I did. This helped me after the placement when trying to explain my project to others, as I could show them distributions, workflows and explanations behind my work.

After my placement, I went back to school and told others of my experience with Nuffield and the NI Centre for Stratified Medicine. My school previously was not aware of these placements, but now they are.

The BT Young Scientist & Technology Exhibition


Although I could have entered my project for the Big Bang Competition, I thought my project on cardiovascular disease risk was more relevant to Ireland. I decided to apply to the BT Young Scientist Competition as it was easier to travel to and more familiar to me.

The whole BT Young Scientist & Technology Exhibition was amazing. The number and range of projects were expansive. The opening event was something that would see out of the Eurovision Song Contest, with lights, cameras and screens everywhere. They even had music, presenters and a talk from Michael D. Higgins, the President of Ireland. The judging was by three judges over three days and based on the report, delivery, methods and explanation of your work.

I was shocked when I found out I was awarded the “Best Impact on Human Health” award from the Royal College of Surgeons Ireland! This award was a special award, and would not be judged normally according to the competition, hence any judges for this would not be identifiable by a judges’ badge – so I did not have a chance to influence them specifically! I felt excited and honoured by such an organisation thinking that my project was contributing to scientific research and that it was of interest to them. I have now been invited by the Royal College of Surgeons to their research day to further explain my work to others.

What an achievement to win such a prestigious award! Are the any reasons that you think your project stood out against the others in the competition?

One of the requirements for winning was to have a project that showed evidence of real research and scientific investigation. My project showed evidence of this as I had to look at the advantages and disadvantages of stratifying/categorising my patients using machine learning models or through other statistical methods. Knowing how you can use what you learned is good, but also knowing the fundamentals behind what you know is even better as you know then the limits of your implementation.

I believe that this journey, starting from a Nuffield Research Placement, and then to show my work at the BT Young Scientist and Technology Exhibition has given me a lot of invaluable knowledge that I couldn’t have gained from any other placement.

What advice would you give about what makes a good placement?

My message to placement providers is that they should make sure that some independent learning or research is carried out on the placement where possible. I think this is important, as problem-solving, management of time and goal management is essential for a student within A-levels for success, but also for future work. An independent project for that student where possible with significant work could also be an option, giving something that the student has authority for, making them put the quality of work at the highest importance for them.

Where are your planning to do next?

I am now looking at Ulster University or Queens University Belfast to study Computer Science. I am also looking at Data Science or Data Analytics as an alternative career choice as it is something that involves the skills I have learned on my placement.

I would like to give thanks to my Nuffield Co-ordinators, Conor Sloan and Karin Walker for arranging my placement. I would also like to thank Dr Steven Watterson, The NI Centre For Stratified Medicine and Ulster University for facilitating my placement and the Staff at Holy Cross College for supporting me throughout this whole journey.