Daniel Collins (Ask-JGI Data Science Support 2023-24)
I applied to Ask-JGI as a 2nd year PhD student on the Interactive AI CDT. Before starting my PhD, I spent several years working in Medical Physics for the NHS. Without a formal background in data science, transitioning to an AI-focused PhD felt like a significant shift. I was looking for opportunities to gain more practical experience in areas of data science outside of my research topic, and Ask-JGI has been the perfect place to do this!
Working with Ask-JGI has been a hugely rewarding experience, and I’ve really appreciated the variety it introduced into my day-to-day work. With a PhD, you’re often working towards a long-term goal in a very specific domain area, with projects that can span several months at a time. With Ask-JGI, each query becomes a self-contained mini-project with a much smaller scope and timeline. These short bursts of exploration and learning have been really valuable to have alongside my PhD.
The queries involve supporting researchers from various specialisms across the University, and can involve a broad range of topics and technical skills. I’ve particularly enjoyed queries that have involved writing demo code e.g. for data processing, visualisation or modelling. One of the highlights has been my work with GenROC, visualising the number of children with different rare genetic conditions recruited to the study. To try to make it more engaging for the children and families involved, we developed a pipeline for creating 3D bubble plots with a space theme using the Blender Python API. This was great because I got to spend time learning a new software tool while also learning more about the important work the GenROC researchers are doing at the University!
I wholeheartedly recommend joining the team if you have experience in any area of data science and you’re looking to develop your skills. The JGI team have created an incredibly friendly and supportive environment for learning and collaboration. It’s an excellent opportunity to learn from others, and gain exposure to the different ways data science can be applied in academic research!