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Roshan Chacko

University of Nottingham

MSci Physics with Nanoscience
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Why did you apply for an internship with Peratech?  

I heard of Peratech in the first year of my degree when I learnt about the company’s invention of quantum-tunnelling composites (QTCs). I learnt about the phenomena of quantum-tunnelling briefly in our Nanoscience module in Year 1, and I have been interested in Peratech ever since. So, when the opportunity opened up for me to apply in the middle of Year 3, I was very excited. I thought that the computational internship was the perfect playground to learn and absorb a coding repertoire, building from my limited experience in Machine Learning (ML) and scientific computing.

What projects are you involved in at Peratech? 

The project that was my focus throughout the internship involved the implementation of AI-based concepts in the design of sensors. Initially, I spent time learning the code and writing supporting documentation and then I was tasked with amending the code itself to make some important improvements that would significantly improve its speed. I implemented a storage method that reduced the amount of space taken up by training data for the AI model. 

What has been the highlights of your internship with Peratech? 

I expected to enjoy experimenting with the code and new techniques most. But at Peratech, especially under guidance from Dr Tim Wiles, I experienced a lot of encouragement and a very constructive work atmosphere. That was the main highlight for me. The other highlight was seeing my improved framework reach the goal level of accuracy. 

What have you gained from your internship with Peratech? 

Completing this internship has given me valuable insight into problem-solving. After experimenting with a bottom-up approach to improve my code and training model’s size and accuracy, I realised I needed to approach the problem in a different way, in a more top-down approach. But the icing on the cake for my internship was Dr Wiles. Dr Wiles offered me lots of advice and constructive criticism throughout my internship, which I took on board. I found this very encouraging, and I intend to practice these as I take on more computational projects in my 4th year and beyond.

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