July 6, 2023, by Prof Meghan Gray

MSc Machine Learning in Science: Elliot’s experience

Guest post by Elliot Hicks, MSc Machine Learning in Science 2022

When I was studying for my BSc in Physics at the University of Manchester, I decided that I wanted a masters that would give me the best possible advantage for entering the field of machine learning. When I came across the Machine Learning in Science masters, it was an obvious fit for me, and I applied the same week.

The MLiS course at Nottingham was the best time I’ve had in academia, the content, staff and projects were fantastic. One of the main things I liked about the course was the consistent freedom in projects – if I wanted to learn about reinforcement learning, I simply chose a coursework that lent itself to a reinforcement learning solution. This freedom not only allowed me to learn the best approaches for applying machine learning to real-world problems, but also allowed me to find what niches of machine learning I enjoyed most.

During my time on the MLiS course, I was fortunate enough to be invited to assist some of the MLiS staff on a project with an external company, Oakbrook Finance. There I went on to research, train and evaluate a cutting-edge NLP model for sentiment analysis. This work provided invaluable opportunities for me as I was able to connect with and present findings to Oakbrook staff in an industry environment. Crucially, this was my first piece of work experience in the field of machine learning and it gave me a huge advantage when applying for positions after I graduated.

Having had the pleasure of working alongside some of the MLiS staff, and being taught by the rest of the team, I cannot recommend them enough. The MLiS staff’s expertise covers a wide range of topics, and they work hard to be available to support students whenever possible. Even now, a year on, I still like to stay in contact with staff from the course (and sometimes I still ask for advice when I’m stuck!)

Following the masters, I secured an internship working as a deep learning researcher where I trained physics informed neural networks for industrial applications. I even got to present to large companies like Google and NVIDIA. Now, I work as a machine learning engineer at a healthcare AI company where I work on computer vision algorithms for medicine. The advantages the MLiS course gave me when joining the industry can’t be overstated, I use the content I learned on this course every day at work. I have no doubt that the wide range of knowledge, skills, and experiences that this course gave me were indispensable to the start of my career.

• Share on Facebook
• Share on Twitter
• Share on Google+
• Share on LinkedIn