In contrast to my post about Pepster, this isn't going to be a year-by-year timeline for my research. Anyone who has done a Ph.D. can probably attest to the sporadic nature of getting from start to finish. Instead, this will be a breakdown of the most important outputs of that work.
First and foremost, the question I get asked the most is, "should I do a Ph.D.?" My answer is almost always "No." Not because I don't think anyone should, but because if me saying no is enough to stop you without question, you probably shouldn't. That isn't meant to be elitist or gatekeeping. A Ph.D. can be a grueling and lonely experience. Unless you have something deep driving you to get it done, it may well be a pretty horrible experience. I had my ups and downs. I would do it again, but seriously, read up before getting started.
My Area of Research
My Ph.D. investigated designing gradient coils for hybrid magnetic resonance imaging (MRI) machines. Quite the mouthful, so let me break that down a little. MRI machines are great for imaging soft tissue in the body (think muscles, organs, and fat). A hybrid MRI is a combination of an MRI machine and some other piece of hardware. In my case, it was a linear accelerator used for radiation therapy. The MRI would scan the patient, find a known target, and use that image to adjust the radiation beam. This combination would mean less radiation in healthy tissue.
As the name might suggest, MRI machines use magnetic fields in the imaging process. This means if there is metal nearby, it can distort the image, or in some cases, cause accidents. We designed an MRI system that integrated with a linear accelerator. Something made up of a lot of metal. Additionally, the MRI and linear accelerator combination required us to split the MRI down the middle to make room for the patient.
My contribution to the literature was new methods to design MRI gradient coils under these conditions. Gradient coils modify the magnetic field to let the machine localize the signal and generate an image. These coils needed to produce a linear field had minimal noise and produced low levels of heat and torque. This involved simulating the electromagnetic environment and running optimization routines on the coil design to generate a final output. Those were then built and verified using a CNC-controlled magnetic sensor.
It was a great project that allowed me to work on software and hardware all at once and develop technology that would help make a difference in the world. If you're curious to read more, you can find most of my work on my Google Scholar page.
How I got started
My undergraduate degree was in electrical engineering. I did a mix of hardware and software design during that time, including some advanced courses in electromagnetics and numerical optimization. During my third year of study, I was asked to help one of the professors with experimental validation. The team had strong physics experience but less lab experience. I helped out on that work with people now at the cutting edge of MRI design at places like Hyperfine.
After we finished that work and published the paper, I was asked to consider applying for a Ph.D. position within the team. The introduction to the lead on the project came through a long chain of introductions. Most of those were possible because I'd been tutoring for first and second-year subjects and spent a lot of time knocking on professors' doors asking for advice on things I was building at the time. I was lucky to have those connections and learned the value of building in public well before that became a coined phrase.
Things I wish I could tell myself on day one
In the years since graduating, I've thought a lot about how I would do a Ph.D. differently if I started today. I went straight into a Ph.D. after graduation. The timing worked out well, and I thought every year away from an academic salary would make it that much harder. Nevertheless, if you're on the cusp of starting one and can learn from my mistakes, that's better for everyone.
1: Read papers and implement them. Seriously.
Like any first-year candidate, I read a lot. I took notes, kept records of symbols and their meaning, and tried to get a clear mental picture of how the world of gradient coils fit together. What I didn't do, was implement them. I inherited an existing code base and spent very little time learning how it worked in the beginning.
If I had my time again, I would write a lot more code. Not because it wasn't there but because there is a different kind of familiarity that comes from doing the hands-on work. I realize not every field will be ideal for this, but there are likely parallels that apply. Get stuck in deep and become an expert in your tiny corner of the universe as fast as you can.
2: You are not your research.
During my Ph.D., I was obsessed. Somewhere along the way, I crossed the line that separated my research from my self-identity. When that happened, I took a bit of a downward turn. Research is about taking risks and trying new things. When those things don't work out, that's learning. In my mind, when those ideas failed, I failed.
This unhealthy blur of my work and personality led me to work too much. I lost a lot of hobbies and sleep trying to make things happen. Looking back, I wish I could tell myself to have more fun. Spend time on exchange, take holidays, live a life that is more than the outcome of my experiments.
There is probably an air of this in my current life. As they say, we write what we need to hear.
3: Don't stop telling people what you're working on
Despite my Ph.D. mostly occurring out of building in public, I quickly became pretty quiet about my work. A mix of the point above and a feeling that my work was too narrow for other people to care.
Late in my Ph.D., I spent a lot more time talking to other people about my work and made many great friends along the way. I took part in the three-minute thesis competition. It was a nice chance to talk about my work and prepared me well for distilling complex ideas into short time frames.
Things I learned beyond the research
While any Ph.D. is narrow, the things we learn tend to be deeper and more general. For me, the work I did prepare me for a life filled with answering questions nobody had asked before. It prepared me to set out into uncertain territory and be okay with not having a clear path to a solution. It taught me how to research deep questions and how to be okay with complex problems. Most of all, it taught me that we all know far less than we imagine and that the days of discovery and breakthroughs are more narrow but still as abundant as the discovery of gravity and the electron.