A picture of Thomas Edwards in front of a green field and trees.
Credit: Thomas Edwards

Why did you choose to study science? What do you like/dislike about working as a scientist?
At school I wasn’t completely sure what career path I wanted to follow and was split between training to become a medical doctor and an engineer. In the UK you need to choose 3-5 subjects to specialise in for the final two years of high school so I chose the various sciences and maths to keep my options open. I ended up deciding that I wanted to become an engineer but I had two fantastic physics teachers who convinced me that if I did physics I could always become an engineer afterwards but the reverse was not possible. At university, I enjoyed physics so much that I wanted to continue and was extremely keen to go on to do a PhD. At that point I had also looked into a variety of career options and discovered that, for many, a PhD was either required or highly desired. So a PhD in a subject I was extremely interested in seemed like a sensible choice!

Working as a scientist has its ups and downs. I think the most exciting part is discussing new ideas with collaborators who you gel with extremely well. The first phase of a project where you brainstorm, come up with a new idea, and implement exciting new science is rewarding. My main dislike about being a scientist is the lack of choice when it comes to which city/town you live. Being a post-doc one often has to apply to many positions (typically only a couple in each city max), which means we have little control over where we are likely to get a job.

What is your field of research?
I work mainly on gravitational wave data analysis and am mostly an independent researcher. My work involves a combination of things: first, theoretical modelling for the signals we expect to see in these gravitational wave detectors; second, developing new algorithms to look for these signals in the huge data sets. My particular focus has been on trying to make sure that interesting signals in the data are not missed. 

To go into a little more detail, one needs to know that the signals we are looking for in the data are completely swamped by the noise. It's really like looking for a needle in a haystack. Fortunately, over the past few decades, extremely sensitive techniques have been developed to precisely extract these signals. So far though, they have been finely tuned to search for the most likely signals which come from the motion of two black holes in a binary system. But it's possible that other, more exotic, objects could form binary systems and be picked up by our detectors. I work on extending the data analysis techniques so that they can be used to find not only black holes, but anything that might be out there in the Universe.

Which of your skills are you most proud of?
I’m don’t think I’m particularly gifted at any one thing. Instead I am most proud of my ability to communicate with a wide variety of audiences from theorists to experimentalists. I try to utilise this skill to look for new research directions that were overlooked in the past.

What new skills would you like to learn in the next year?
I’ve become interested in how machine learning and artificial intelligence can fuel scientific discovery. Over the next year I’m hoping to learn more and integrate the use of machine learning directly into the work I’m doing. In addition, physics has a lot to offer the world of machine learning (complex but accurate simulations and deep theoretical understanding to name a couple) and I hope that my work can also contribute to the field of machine learning itself.

What advances or new results are you excited about or looking forward to?
The work I’ve been doing for the last two years on searching for new signals in the gravitational wave data is extremely computationally demanding and therefore difficult. Machine learning has the potential to completely change this by drastically cutting the computational cost of processing gravitational wave data. The hope is instead of running our algorithms on large supercomputers, we can do the same thing on just a small laptop. I’m excited to see how this line of research evolves!

What's your favorite food?
I’m an avid cook, and spend a lot of my time scouring cook books for new recipes. I’m a particularly big fan of the chef Yotam Ottolenghi and have been slowly making my way through almost all the recipes of his various books. That being said, my main comfort food is pasta with a simple tomato sauce and some good cheese!

How do you relax at the end of a work day?
Relaxing at the end of the work day has become more tricky with working from home for the past two years. I try to either go for a run or do some other form of exercise (not always successfully) to split the work day from the evening. Over the past couple of years I’ve also become much more interested in playing video games! I’ll often spend a few hours each week playing some sort of playstation game.

What do you hope to see accomplished scientifically in the next 50 years?
Over the next 50 years, there are a few things that I hope to see happen. In the realm of physics, I hope that we discover something from beyond the standard model of particle physics. I’m pretty agnostic about where that discovery is likely to come from, but I think a major unexpected discovery in particle physics is overdue and would really benefit the community. I would also like to see machine learning and artificial intelligence fulfil its promise. At the moment, there is a lot of hope that machine learning will solve a whole host of issues throughout science. I hope that this proves to be true and that the scientists will benefit from research into machine learning.