Curriculum Vitae
Between SecureBio’s founding in 2022 and 2024, most of the people working on biosecurity in the Sculpting Evolution group at MIT gradually moved over to work at SecureBio instead. I was one of the last people to make this transition, formally making the jump in February 2024. Since then, I’ve continued my work on the Nucleic Acid Observatory as a Senior Research Scientist, managing several other researchers and a large chunk of our computational infrastructure. In addition to continuous development on our public MGS pipeline and several private pipelines, I’ve also led a number of publications, grant applications, and other projects, as well as overseeing most of our hiring and a range of other operational and governance duties.
In 2022, I moved to Massachusetts to start working on the Nucleic Acid Observatory full-time. I played a major management and co-ordination role in the early stages of the project, with lots of work on strategy, hiring, and partnerships as well as actual research. Some major achievements I’m particularly proud of during this time include starting a partnership with Ginkgo Biosecurity and CDC to investigate airplane wastewater metagenomics; several reports on biosurveillance and biosecurity strategy, some public and others for private government stakeholders; and hiring and managing several awesome teammates, many of whom are still with us. I also played an advisory role in setting up SecureBio, an independent biosecurity and biodefense nonprofit, and became its founding Secretary.
Towards the end of my time at MIT, as we began collecting metagenomic sequencing data in earnest from several different sources, our need for bioinformatics and data-science expertise became more acute, and I began putting a larger fraction of my time back into technical computational work. This included early work on what would become our primary MGS analysis pipeline.
After I left altLabs (see below), I spent some time as an independent consultant working out of Oxford, UK, consulting on various biosecurity projects. It was at this point that I seriously reconnected with Kevin Esvelt and started doing early work on the Nucleic Acid Observatory project, along with some work with former altLabs folks on the California Pandemic Early Detection and Prevention Institute Initiative. After a while, I decided to join the Kevin and the NAO full-time.
Based partly on the strength of my performance on the contact tracing project, the founders of altLabs, a newly founded biosecurity nonprofit, contacted me to ask if I could lead their Genetic Engineering Attribution Challenge, a data-science competition aiming to advance the state of the art in applying machine learning to identify the origin of engineered sequences. This was a very different job from anything I’d done previously, far more focused on project management than research, and I learned a lot very quickly about managing schedules, coordinating different stakeholders, and public relations. I made a bunch of strategic and implementation decisions; managed our relationships with the competition platform, our co-sponsors, and our judges; did my first ever media interviews; and generally kept everything spinning.
The competition was ultimately a big success, substantially improving on the previous state of the art and resulting in another Nature Comms paper (co-authored with Olly Crook). Sadly, after the competition everyone involved ended up moving on to various other projects (many of which I remain very excited about!), and I’m not aware of any public work since that’s really built on that legacy. (altLabs has since shut down.) That said, I did learn a bunch about this and related areas of biosecurity, as well as building up a bunch of useful management skills, all of which I took on to my later work at the Nucleic Acid Observatory.
After things wrapped up with WAI, I was left at a bit of a loose end, trying to figure out what I wanted to do next with my career. I spent some time working on the manuscripts from my PhD work, some time studying data science and machine learning like everyone was in 2019, and a lot of time agonizing about what I wanted to do with my life. At some point in the middle of all this I got a grant from the Long-Term Future Fund to do some work on information hazard strategy; this never really went anywhere and I ended up returning a good chunk of the money later in the year.
I was clued in enough to the biosecurity world to get spooked pretty early about COVID-19, and was contacting friends and loved ones about it by the end of January. By March, I was locked down in my parents’ house trying to think if there was some way I could help. Working my biosecurity contacts, I got put in touch with Kevin Esvelt, who was looking for someone to lead a research project on improving contact tracing. I dove into this with abandon and put out a preprint within three weeks, which ended up turning into a Nature Communications paper. A lot of other opportunities flowed from my performance here.
Between the contact-tracing project and my work at altLabs (see above), I was a Summer Research Fellow at the Future of Humanity Institute, where I mostly worked on dilemmas of openness versus secrecy in genetic engineering detection and attribution. This work didn’t end up getting published but was labeled “outstanding” by a major funder in the field, and helped guide my later work at altLabs and the NAO.
I left my PhD with a yearning to explore, a deep desire to spend a while far away from academia, and no other plans. To pay my travel costs and try something new, I applied for a part-time remote role as a research intern at Wild Animal Initiative, a research and field-building nonprofit I still believe is super-cool. Pretty soon after I arrived, leadership and I agreed it was pretty silly to call the only person in a research org with a completed PhD an intern, so I got a free upgrade to Research Fellow.
My time at WAI was brief but fun. I primarily worked on a big literature review on biomarkers of ageing as welfare indicators, a field that managed to combine my PhD expertise with a topic I and WAI are both very interested in: measuring welfare in non-human animals. The resulting report was, in my opinion, pretty cool, and landed me a speaker spot at Effective Altruism Global London 2019. That talk got a fair bit of buzz and obliged me to tell various disappointed animal-welfare folks that I sadly wasn’t staying in the field.
I typically tell people I did my PhD in Germany, but this is technically a lie; I don’t have a PhD, I have a Doctor rerum naturalium, the standard German equivalent. While this has a way cooler Latin name and is much more appropriate for my actual expertise, it also tends to confuse anglophones, so I usually save everyone time and just say “PhD” instead.
To get my technically-not-a-PhD, I moved to the ugly-but-friendly city of Cologne, Germany, where I joined the Cologne Graduate School of Ageing Research and the laboratory of Dario Valenzano (now at FLI Jena). There I studied B-cell ageing in the turquoise killifish, a competitor for the shortest-lived vertebrate species (and hence great for studying vertebrate-specific ageing processes like those in B-cells). I characterized the structure of the immunoglobulin heavy-chain locus in the species, then used immunoglobulin sequencing to investigate how B-cell populations in the species change over lifespan, finding that B-cell repertoire diversity declines significantly with age - the first such finding in any species.
Along the way, I learned a bunch about doing data science and bioinformatics in Python and R; workflow orchestration in Snakemake; a range of specialised bioinformatics tools for analyzing sequencing data, assembling genomes and building phylogenies; and a bunch of field-specific knowledge I don’t anticipate making much use of in my future career. I also learned a whole lot of wet-lab techniques that I also don’t intend to ever do again, but which it’s useful for me to know about when helping plan experiments, analyzing data, and understanding published results.
(I also learned pretty good German, but that’s sadly now much-decayed.)
After my Bachelor’s, I stayed on in Cambridge for an extra year to learn more about computational biology. Unlike my BA, this course was, objectively speaking, not very good. However, I did learn quite a lot of R and how to correctly pronounce “De Bruijn graph”.
For my Master’s thesis, I interned at Genestack, a Cambridge-based bioinformatics company. This was my first work experience outside fo academia and my first experience coding in Java, which I hated. Much more usefully for my future career, it was my first experience coding collaboratively with Git and Github.
In 2010 I matriculated at Queens’ College, Cambridge to study Natural Sciences. Cambridge has a very mix-and-match approach to science study, but I stuck very determinedly to biological subjects throughout my time there, taking subjects like Biology of Cells and Animal Biology and eschewing those like Physics and Earth Sciences. I spent my final year in the Zoology Department, and finally got to live out my dinosaur-kid dreams with a real-life palaeontology project for my final-year dissertation. (Unfortunately, real-life palaeontology turned out to require a higher tolerance for boredom than I was able to sustain.)
Along the way I received various shiny prizes, including yearly College Prizes for my academic results, two prizes for “outstanding distinction” in the biological sciences, and two others for lower levels of distinction, less enthusiastically phrased but still presumably fairly distinctive.
In 2012, I spent the summer as a Janelia Undergraduate Scholar in Virginia, my first experience of research abroad and my first time in the US without my parents. My deep embarrassment at my total lack of programming skills while there spurred a lasting pivot towards computational biology and bioinformatics.
Queens’ was also, somewhat appropriately, the place I came out to all and sundry for the first time. For this and many other reasons, it remains a place for which I hold deep affection, despite the fact that I was objectively quite depressed for the second half of my time there.
A-levels are the time in English education where you’re supposed to whittle down to only a few subjects and really start to specialize. In my case, this principle was rather disrupted when I read The Selfish Gene in Year 12 and was inspired to study biology at university. Unfortunately I wasn’t studying chemistry at the time, which is an essential prerequisite for any serious university course. Cue a lot of reshuffling and extracurricular tutoring to get me a two-year qualification in half the time.
As a result, in addition to my A-levels in Biology, Chemistry, English and Maths, I also have three dangling half-A-levels (known as AS levels) in other subjects. One could see this as a demonstration of impressive breadth or unimpressive indecisiveness, depending on your perspective.
My GCSEs were so long ago now that I had to look up an ancient CV to find out what subjects I took. It was a lot of subjects! Triple science, double English, maths, Latin, German, history, religious studies. I got A* grades in everything except German, where I got an A. That A meant I missed out on a school prize for straight-A*-students, a fact that 16-year-old Will found deeply unjust.
In Year 11 I badly injured my ankle and got to skip rugby for a whole season because running caused me intense pain. This was a highlight of my year.