Michelle completed her bachelor honours degree in plant biotechnology and genetics at the University of Guelph in Canada. She worked in plant breeding programs during this time in both industry and academia. She came to Australia on a student exchange at the end of her degree and decided to stay. She did a working holiday visa, where again she worked in plant breeding programs at various universities across Australia, which eventually led her to an international PhD scholarship at the University of Sydney in plant pathology and bioinformatics.
During her PhD, she undertook the Inventing the Future course for postgraduates, which led her to co-found the AgTech startup Carapac. During this time, through networking events, she met the founders of another early-stage startup, called BioScout. She ultimately left Carapac a couple of years later in favour of finishing her PhD. However, shortly after she graduated, given her experience in plant pathology and startups, she was headhunted for the role of Head of Science at BioScout, where she remains to this day.
I have always been passionate about using science in an applied way to make the world better, and this is exactly what we do at BioScout. We develop and use cutting-edge technology to monitor airborne diseases in near real-time, and I get to apply my skills in plant pathology to ensure that our data is used to help growers make the best decisions possible. Overall, our aim is to make agricultural disease management both more sustainable and more profitable for growers. It's a job that's easy to be passionate about.
Curiosity is the cornerstone of scientific exploration, and I believe this trait is what drives most people to this profession. There are so many ways in which you can cultivate it, so I'll suggest one: don't be afraid of failure. In our typical education systems and academia, failure is treated as something to be avoided. You get punished for bad grades, and you can't publish failed experiments. But failure is how you learn, and this needs to be celebrated. To fail badly means you had the courage to try something you weren't certain would work, which is more than most people ever do.
I wouldn't be where I am today without the learnings from a startup I wasn't able to continue. It hurt at the time, certainly, but what I learned from that is invaluable. And ultimately, I really benefited from it in the long run.
Challenge all of your assumptions. In agile environments like startups, we are strongly encouraged to ask questions and talk to as many people as possible, particularly those you see as your end-users and involved in your supply chains. Often, problems are more complex than you think, and a useable solution isn't always straightforward. You don't know what you don't know. You need to challenge your assumptions about what the problem really is by talking to the people you are aiming to help, and see what really matters to them.
Once you think you have something that can solve some real problems, you need to get out again to make sure your solution is actually user-friendly and what people need. Don't just make assumptions. Get real information, and real criticism, about what works.
I ended up finding a career that matched very closely to what I researched in my PhD. So in this particular case, I would say the rabbit holes I went down as a PhD candidate studying epidemiology of cereal rust diseases has given me an excellent foundation of knowledge that I use regularly in my role at BioScout. However, for researchers looking to transition into industry, this will not often be the case.
With this in mind, I would say the best transferrable skill I gained is the ability to learn. I couldn't write a single line of code when I started my PhD, yet I ended up graduating as a competent bioinformatician a few years later. It was a hard slog, but I persevered. In my role as head of science, I am constantly faced with huge challenges involving tasks I have never done before, and it feels like I'm always hitting a big learning curve with something, be it managing multi-national projects or processing tech debt. However, I always remind myself that if I can go from 0-to-bioinformatician in the time I did, then I can certainly do this.
Real boats rock. Give me a project that is running smoothly, and I will give you someone who is likely lying about their project. Industry and academia face very different pressures as they have different funding models, mentalities, and success metrics. But one thing is constant: you will have projects where things will go horribly, horribly wrong. I used to think it was just me, until I talked candidly to enough people and they inevitably opened up about their own experiences where everything seems to be on fire, and not in a good way.
So the main lesson from this is: never expect things to go smoothly. You will have issues. That is ok, and completely normal. You should be planning your projects with buffer time and backup plans for when things don't work out as they should. Your goal should not be to run every project perfectly; that way lies madness. Rather, your goal should be to always find a way forward despite the inevitable.