My name is Ramya Gurunathan and I’m a current student in the MPhil in Scientific Computing, focusing on the atomistic modelling stream. Prior to arriving in Cambridge, I studied materials science and engineering in the United States. My desire to travel across the Atlantic Ocean to study in this program came as I began to recognize the importance of high-performance computing, machine learning, and multiscale modelling in materials science research. I was excited, therefore, to discover a program that would expose me to computational techniques and allow me to apply them to interesting scientific problems under the guidance of experts.
The courses I was enrolled in covered a wide gamut of skills from computer hardware to numerical analysis to modelling of quantum mechanical systems. Our professors came from different departments and represented both academia and industry. I was heartened by the ways my professors showed that they cared about my student experience. Many of them continuously asked us for feedback and were quick to offer individual meetings or even Skype appointments to go over coursework.
As I start on the research portion of the MPhil program, I’m excited by how much input I have had on the project I will work on. My research advisor worked with me to design a project that piques my scientific interests and utilizes techniques that I am keen to master.
My interests in science and technology led me to the MPhil in Scientific Computing at Cambridge. Coming from a chemistry background, the wide variety of courses taught by lecturers from many different fields have deepened my knowledge far beyond what I would have learned from a Chemistry PhD and broadened my perspective on computational sciences. Another contributing factor is the students; there are few enough to feel personal, but there is no lack of diversity in backgrounds. This program in particular is uniquely based in the sciences and is attuned to my interests, unlike many other programs based in mathematics. My perspective has also broadened beyond pure academics.
The Centre for Scientific Computing serves as a hub for collaboration between the world renowned academics and the technology industry for which Cambridge is famous, an interplay I had never witnessed until now. The course is fast-paced, but deadlines are reasonable and I am constantly impressed by the rate, and breadth, of my accomplishments. I look forward to applying a vast and unique insight on scientific computing to problems in chemistry.
The MPhil in Scientific Computing provided a crucial bridge between my first degree in Theoretical Physics and the computational research that I now perform as part of my PhD. The breadth of my particular field, atomistic materials modelling, has grown rapidly in recent years with increasing availability of computational resources --- it would have been extremely hard to choose a particular research direction without already having the direct experience the MPhil provided. After 3 months of lectures, two short research projects allowed me to explore my interests in the field and begin to focus the future direction of my PhD towards something with direct experimental significance, the modelling of battery materials. Despite the short amount of time available, the projects provided a vital opportunity to play with various methods without the often debilitating freedom of open-ended research. These methods then carried through to the 6 month project which could be specifically crafted to my interests. I use the software tools that I developed during my MPhil daily to accelerate my current work, tools that I may not have been able to dedicate the required time to develop during the PhD alone. Studying for the MPhil also immerses you in a diverse community of computational researchers --- engaging with researchers in other fields helps propagate generic best practices that can be applied to your own work. This community extends throughout physics, chemistry, materials science and engineering, in Cambridge and beyond, and with it possibility of forming strong links with experimental groups to maximise the relevance of computational work.
I completed the MPhil in Scientific computing, as the first year of the CMMS CDT, two years ago. The course helped me feel more prepared to start my PhD with the lecture courses providing me with necessary knowledge of atomistic modelling and electronic structure techniques, whilst the six month project improved my research skills and general ability to manage my time. All of this meant that I could begin my PhD research promptly, without spending vast amounts of time reading or learning basic skills. An additional benefit of the MPhil was having a collection of students, with common research interests, from a range of different departments. This has meant I now have a wider idea of the work that is carried out across the university and strong links exist between students in the engineering, chemistry, materials and physics departments.