Faced with the intimidating landscape of the job market, I was eager to gain work experience during my first-year university summer. The opportunity to return to a company I had worked with before seemed like the right way to start. My name is Orla and I’m a first-year physics student at the University of Bristol, coming to the end of my work placement at Think.
What initially appealed to me about a summer internship here was the opportunity to further my knowledge of the aviation industry. Hearing that my project would focus on a computer vision detection solution for tracking aircraft at an airport only made me more eager to get involved with this emerging subfield of machine learning. Having completed my Year 10 work experience at Think four years ago, I was confident my return to the Branksome office would be a smooth one. Upon arrival, I was welcomed into the team and given some more background on the project and introduced to the project mine would follow on from.
The project was to define the requirements and start development of the computer vision algorithm for aircraft tracking at an airport using Python. I was able to build on the developments from previous projects. This allowed me to understand the mechanics behind detector model training and image processing before adapting relevant pieces of work for my own project. Seeing how utilising pretrained models could speed up machine learning processes demystified a lot of the functions behind systems reliant on artificial intelligence.
We first developed a two-camera stitching algorithm to be able to generate a wider field of view for the detection solution. The iterative process for the camera calibration brought a lot of satisfaction. After carrying out background research into computer vision, it was exciting to see the individual steps of pre-processing (correcting lens distortion and differences in exposure) applied to a dataset taken by cameras I had set up myself! Several of the following steps also gave me the opportunity to deepen my understanding of existing work: one Jupyter notebook on homography and warping led me to research geometric transforms and tensors, which linked back to fundamental mathematical concepts I was introduced to during my first year at university.
Considering the challenges that came along with practical implementation of a computer vision system encouraged me to investigate other methods of algorithm optimisation by filtering the inputs. Running quantitative validation on the outputs of the code allowed me to direct my efforts to the stages that needed the most improvement. Next, using a trial dataset, I was able to refine the requirements set at the start and test the capabilities of computer vision for aircraft on a runway. This dataset could also be used to test code for threshold crossing detection and tracking an aircraft’s movement across an airport.
The opportunity to attend a quarterly staff day gave me insight into the other lines of business that Think handles and enabled me to understand projects my co-workers were part of, which had previously been a mystery to me! Sitting in on other accounts’ weekly and quarterly meetings allowed me to get a glimpse into the business management side of Think and see how clients and contracts are planned and obtained. Beyond acquiring the required technical skills to complete the project, this internship also gave me the invaluable opportunity to learn interpersonal skills fundamental for success in any career path.
The project has been structured in a way that has given me the best possible output, including hitting all the deliverables laid out at the start, whilst also being relaxed enough to give me the autonomy to conduct my own research into connected topics. Informal daily catch-up meetings helped move the project in the right direction, and these discussions often led to quick solutions for any setbacks that cropped up.
The willingness of others to help me despite having other commitments is what has made my placement here so productive, and the specialist guidance from other team members is something I am very grateful for. My time at Think has been comprehensive and will continue to serve me after the completion of my project, making a summer internship here one I would recommend to any fellow university student looking to gain work experience.
Orla Ring | Summer Intern 2026