I am a 2nd-year PhD student, working as part of the Gravitational Waves group. Gravitational wave data analysis is a relatively new field of Physics, although the theory has been thoroughly studied since their prediction in the early twentieth century. Since the first observation in 2015, we have observed more than 10 black hole mergers (and one binary neutron star merger) across the first two observing periods, with more than 50 additional candidate signals in the (ongoing) third observation.
Having started in October 2018, my research is currently looking into the extent to which we mismodel the data when we make compromises for computational efficiency, and the effect this has on our results. While it is currently assumed to produce results 'close enough' to correctly modelled data, the effect will become particularly important to study the longer signals we expect to see when the Einstein Telescope begins observing. I have been working with the PyCBC Inference code, and I hope to make a contribution to this code towards the end of my PhD.
I studied Theoretical Physics at Royal Holloway, obtaining a first-class MSci in 2016. My modules were typically related to cosmology or condensed matter physics, with my final year project being a stufy of the two-step condensation of Bose-Einstein condensates. Among the various skills I developed, it was my first experience programming – specifically, using Python, Mathematica, and MATLAB.
Upon graduating, I worked for several years as a data analyst in two different jobs, working with both public health care data, and private company data for marketing automation. These years were an opportunity to handle messy datasets and apply techniques gained at university to real life scenarios, as well as being able to work in much larger and more diverse groups. At these jobs, I lead several training workshops and presented to a variety of people from different experiences and backgrounds.