Many researchers feel pressure to make major career decisions before they feel ready. We spoke with Matthew Betts about how career experiments for researchers can help approach uncertainty differently, through small, low-risk steps instead of one high-stakes leap.

What’s your academic background and how did your career path evolve into what you do today?

I’m a neuropharmacologist by training and spent 17 years in academia, with the last 12 focused on clinical neuroscience, using brain imaging for the early detection of neurodegenerative diseases. My most recent role was as a PI, leading my own research group studying neuromodulatory systems in ageing and Alzheimer’s disease. For many years, the goal was to become a professor, but when I became a PI, I started to question whether it was actually what I wanted.

At first, I ignored it. I’d invested so much time and energy into building an academic career that it was hard to accept that I might want something different. Walking away felt hard to comprehend. But the signals didn’t go away, they just got louder. Around that time, COVID hit and everything came to a standstill. It was the first opportunity in a long time to zoom out and reflect on what I really wanted to do. I realised I needed to allow myself to explore alternative paths.

I started small. I thought about what I was curious about — startups, writing, and consulting. So  I began reaching out to co-founders in health tech and joined meetups in Berlin. I managed to get a part-time role at a startup working as a scientific editor. I took on small consulting projects related to my research and began writing about my experiences in academia on LinkedIn.

Each of these steps gave me an insight into what an alternative path could look like and sparked my curiosity about entrepreneurship. That ultimately led me to start MJB Consulting, where I now work with scientists and mid-career professionals navigating similar transitions. A big part of what I do is helping people navigate career uncertainty by leading with curiosity over fear, and using small experiments to explore what might fit.

Career uncertainty can feel deeply unsettling, especially for researchers. Why do you think that is?

I think it’s partly because of how we’re trained. In academia, there’s this implicit idea that if you follow the expected path, do a PhD, then a postdoc, publish papers and secure grants, there’s a clear path forward, even though a professorship or permanent position is rare and highly competitive.

When you start to question whether that linear path is really for you, you’re suddenly faced with open-ended uncertainty. Without that clarity, it can feel easier to stay where you are than to step into the unknown.

Over time, being an academic can become closely tied to your identity. So when you consider leaving, you’re not just changing jobs, you’re letting go of a version of yourself. You start asking, “Who am I if I’m no longer an academic?”

On top of that, stepping into something new often means becoming a beginner again. That can feel deeply uncomfortable, even threatening to your identity. It requires a level of vulnerability to say, “I don’t know what I’m doing,” especially when you’re the oldest person in the room.

You propose a curiosity-driven approach to career transitions, framing them as experiments. What does this mindset shift look like in practice?

Rather than treating a career transition as a single high-stakes decision, I encourage people to approach it as a series of small experiments.

A career experiment is a small, low-risk activity designed to test a hypothesis and learn something new. The goal isn’t to land your next job (yet!), it’s to gather insight.

The experiments you run can lead you down curiosity-driven rabbit holes and open up paths you might not have considered before. And just like in the lab, some experiments will confirm your hypotheses, while others will challenge them.

Where people often get stuck is by jumping straight to big questions too early. Should I leave academia? Should I go into industry? What’s the best option? These questions are often too big and too abstract to answer upfront.

An experimental mindset reframes this. Instead of asking, “What should I do?”, you ask, “What am I curious about, and how can I test it?”

So rather than deciding you want to work at a biotech startup, you might initially explore what that environment actually feels like. You could speak to people in those roles, observe how they work, or find small ways to get involved. It breaks a large, uncertain decision into something more manageable.

Instead of making a leap, you suggest designing small, intentional tests. How would you go about crafting a personalised, low-risk career experiment?

I think about this in four steps:

Observation

It’s easy to jump straight into running an experiment without getting clear on what you’re actually testing. So first, take a step back and reflect on your current situation. If you’re considering a transition, what’s driving that? What’s your energy towards work right now? What gives you energy, and what depletes it? What are you curious about? Has something you’ve read or a conversation you’ve had sparked your interest?

Hypothesis 

Next, form a hypothesis. How could your situation be different? For example, you might be interested in bringing your research into a real-world setting. Your hypothesis could be: am I interested in entrepreneurship, or do I enjoy translating research for broader audiences?

Data Collection

Then, define how you’ll test that hypothesis and for how long. For example, you might reach out to one person every Friday for six weeks for a virtual coffee chat. Or you might dedicate two hours a week for three months to exploring internship or volunteering opportunities.

Analysis

Finally, analyse the results of your experiment. How did it feel? What surprised you? Were you able to stick with it? If not, what got in the way? Try to reflect on the results without judgement. The goal isn’t to prove yourself right or wrong. What might feel like a “failed” experiment can be just as valuable because it helps you rule things out.

A key element of your approach is informational interviewing. How can this be used more deliberately as structured experiments rather than causal networking?

Coffee chats are a great, low-pressure way to explore different career paths, and a bit of structure helps you get the most out of them. Similar to any other career experiment, it’s important to first reflect on your current situation and define what you want to test. For example, “I think I might enjoy a role in medical affairs.” From there, you use your conversations to collect data to test that hypothesis.

Just like in the lab, you need enough data to draw a meaningful conclusion. So aim to speak to a few people in similar roles, not just one. Ask consistent questions so you can compare answers. For example: what does your work look like on a daily basis? What do you find challenging in your role? What surprised you most? How did you make the transition from academia?

Pay attention to your internal signals during the conversation. Are you curious, disengaged, energised?

When you approach these conversations in a structured way, patterns start to emerge across multiple interactions. Without that structure, it’s easy to speak to a few people in “industry” and still feel unclear about what to do next. But when you’re intentional about what you’re testing, you can use what you learn to inform your next step.

Once an experiment is complete, how should researchers interpret the results, especially when an outcome feels inconclusive or “unsuccessful”?

Similar to research, not every experiment will confirm your hypothesis. But the results are still useful because they help narrow things down. The same applies to career experiments.

If something didn’t feel right, that’s valuable data. It tells you what to deprioritise or refine. Maybe you liked parts of a role but not others. Maybe your experiment was too ambitious and you abandoned it halfway through. These are all useful insights for refining your next experiment.

I often encourage people to reflect using something simple like: what worked, what didn’t, and what will I try next? You might not get clarity from a single experiment, but the goal is to build direction through iteration.

Many people start experimenting subconsciously, but without a clearly defined endpoint and a moment to reflect, it’s harder to make sense of what you’ve learned. Taking the time to analyse your results turns the experience into something you can actually use to move forward.

What would you say to those who are still hesitating to explore alternatives to academia?

I think a big reason people hesitate to explore alternatives to academia is the internal narrative that comes with it. There can be a sense of, “If I step away from academia, have I failed?” or “I’ve invested so many years into this, I can’t just walk away.” On top of that, it’s not always clear how your skills and experience translate into roles outside academia.

Sometimes when I suggest running career experiments, people say they don’t have time. And I get that. But my response is always to make the experiment smaller. It doesn’t have to be a big commitment. It could be 30 minutes a week. And if you really don’t have time for that, then it’s worth asking whether your career is actually a priority right now.

The key point is that you don’t need to have everything figured out before you start exploring. You can explore in parallel. You can have conversations, try small projects, and test ideas alongside your current role. Starting small is often the most effective way to reduce uncertainty.

And it’s also important to say that career experiments aren’t just for people considering non-academic career paths. They’re just as valuable within academia. Whether you’re interested in becoming a PI, curious about teaching, or trying to understand what kind of leader you want to become, experiments can give you a sense of what that path actually involves.

Looking back at your own transition, was there a particular experiment or moment that fundamentally changed how you thought about your career?

There was a specific moment in 2022 that changed how I saw my career path. I signed up to a hackathon and, together with two people I’d never met, we developed a concept for a solution to support caregivers looking after family members with dementia. We ended up winning second prize, and riding that momentum, we applied to a startup incubator to develop the idea further. Within two weeks, we’d secured a place to work on the app full time.

It didn’t work out for a number of reasons, but the experience fundamentally changed how I thought about my career. It was the first time I could genuinely see myself doing something outside academia, and it sparked my curiosity to explore entrepreneurship more seriously.

More broadly, it was a lesson in how important it is to put yourself out there and allow yourself to explore. By following my curiosity, I challenged the belief that academia had to be a forever career. I gave myself permission to explore new paths, and realised that career exploration doesn’t have to feel heavy. It can actually be energising, even fun!