­The Career Path Is Not a Straight Line (and That Is the Point)

Andrei Mihai

At a gathering built around extraordinary achievements, one of the most useful lessons for young researchers was strikingly ordinary: A good career does not require a perfect plan. In fact, imperfect decisions are very much part of a healthy process.

That message emerged during a career panel at the 13th Heidelberg Laureate Forum, a panel which brought together people who had moved through academia, industry, start-ups, education, and science communication. While their careers looked very different, the message was strikingly coherent. Careers rarely unfold as a sequence of perfectly optimized decisions.

The Myth of the Irreversible Decisions

You could hardly have a more diverse career mixture on the panel.

At 22, Letiția Pârcălăbescu thought she would continue in physics. She now researches artificial intelligence at Aleph Alpha Research. Katharina Schäfer trained as an aerospace engineer and imagined a future in that field; today she leads academic partnerships at SAP. Rachel Thomas once decided to leave academic research, spent decades in mathematical science communication, and has now returned to research through a PhD on large language models and science communication. Tony Feng followed a comparatively conventional academic route into mathematics, but now splits his professional life between UC Berkeley and Google DeepMind. Dag Ivar Furevikstrand left a lucrative private-sector engineering career to teach mathematics and physics in a Norwegian secondary school, winning a prestigious prize in the process.

For Thomas, the problem once appeared to be a binary one. You were either inside academia or outside it. But that changed with experience.

After leaving mathematical research, Thomas worked in industry and then in science communication. For more than 25 years, she has helped communicate mathematics to non-specialists through Plus magazine at the University of Cambridge. More recently, curiosity about the effect of large language models on her profession pulled her toward research again.

Looking backward, she says, made the branching possibilities of a career much easier to see.

“I think the nice thing about looking back on your life is you suddenly realize you could have gone lots of ways, and it’s all fine. You’ll just find your way. You don’t have to worry that this is a decision you’ll get right or wrong. You’ll make a decision. You’ll see what it’s like, and then you’ll decide what to do next,” Thomas said during the panel.

Schäfer remembered feeling something similar after her PhD. She had studied aeronautics and could have continued along a route closely aligned with that expertise. Instead, she eventually joined SAP, a move she worried might close doors behind her. That did not turn out to be the case.

She told the young researchers that she had once felt she needed to make a defining choice and then live inside it. “But I can take the fear from you. That was a mistake, it’s not right,” she said. Her advice was not to avoid commitment, but to commit to the work in front of you while remaining curious about what might follow.

The idea of keeping every future possible is a tempting one, but it’s also a double-edged sword. The cost of endless optionality is that it can stop someone from going deep enough to become genuinely good at anything.

Pârcălăbescu, whose own path ran from physics through programming into AI research, pushed directly against the idea that a young scientist should preserve every possible option.

“It’s important to not be rigid. You need to look around and see what’s happening and be adaptable to change. Because yeah, be open-minded, but you don’t need all possibilities. The day has 24 hours. I would love to do everything, but I can’t. So just some options are okay, right? You don’t need all options,” she said.

Feng echoed this idea. Flexibility should not mean refusing to choose, but rather refusing to assume that one career choice will determine everything that follows.

Some Skills Are Not In the Syllabus

The discussion eventually moved from where to work to a different question: What does a researcher actually need to be good at? Surprisingly or not, the panel zoomed in on one common thread. It is not AI, and it is not any particular research skill.

Rather, it is human-to-human communication.

Schäfer recalled finishing engineering studies with little experience giving presentations, only to enter professional life and discover that communicating ideas was central to getting anything done.

“You have a good idea, and in industry especially, it will never be realized if you cannot present it in the right tone to the right people. You have to find the right moment to talk to the right people in the right way, right? You have to find the right supporters,” she said.

Feng pointed to another side of communication, understanding people and diversity. We interact with different people, and they all have different ways of communicating. Supervising students or working with colleagues means recognizing that different people respond differently to encouragement, criticism, and pressure.

Pârcălăbescu was even more emphatic. Academic training, she argued, can encourage researchers to believe that excellent technical work will somehow advertise itself.

“It’s a bit of a bummer that we’re all talking about these soft skills, these things that we cannot just measure very well. It would be so much easier for us to say, yeah, you have to be really great at solving differential equations, and then we just start doing that and get good at it, and it’s all good. But it’s this weird fuzzy communication thing that we’re all talking about, and I can just subscribe to that. Getting something done, getting people on board with something, getting a promotion, it’s not about you solving cancer. It’s about people knowing that you solve cancer,” she said.

Growing up and going to school in Romania, Pârcălăbescu said she received virtually no public-speaking experience. When she arrived at university in Germany, she found herself surrounded by students who seemed far more comfortable presenting. She struggled with severe stage fright.

So, she manufactured ways to practice. She volunteered for seminars, teaching, and tutoring, repeatedly putting herself in situations where she had to speak. Her broader point was that university training will not necessarily supply every skill a researcher needs. Sometimes researchers have to identify the gap themselves and deliberately step into situations that make them uncomfortable.

Some Days, “Adequate” Is Enough

Perhaps the most striking point of the panel was a counterintuitive one.

The HLF brings exceptional young researchers into rooms with recipients of the Fields Medal, Abel Prize, ACM A.M. Turing Award, and other major honors in mathematics and computer science. Excellence is not exactly a scarce commodity there.

But no one can be excellent every single day. Being excellent overall and being excellent every single day are two very different things.

“You don’t always have to be the best. Sometimes to be resilient and to learn, particularly to do something you feel uncomfortable with: Turn up, do your best, do the job. It’s okay. I have many days where I turn up and I do the job and I go home. It doesn’t always have to be about ‘I’m going to do the absolute best.’ I personally find that incredibly paralyzing to have that pressure. Sometimes it’s just about doing it, doing it better than maybe last time,” Thomas said.

Summarized, her philosophy was simple, useful, and actionable: “turn up and be adequate.”

Furevikstrand’s story offered an unlikely illustration. Before becoming a teacher, he had what he described as a dream job in private industry, with good pay and strong prospects. Yet he could not shake an attraction to teaching. Becoming the father of triplets sharpened his thinking about what he wanted from work.

Eventually, he went with his gut feeling and left the industry.

“And the people around me, when I told them I’m quitting here in the industry and starting teaching students in upper secondary school, they were like ‘what’? What are you doing? You’re going to lose a lot of money. I know, I know, I’m going to lose a lot of money. But for me, it was the right place to work with the future engineers, the future people to end up with academia and industry, shape them at the early stage, light an interest for mathematics. That’s where I belong, even though the salary is much lower. That’s what gave work life meaning to me,” he said.

This year, Furevikstrand received Norway’s Holmboe Prize, a major national award for mathematics teaching. He told the HLF audience that he had not known he had been nominated. On the day the award was revealed, he had just finished teaching a mathematics class and even thought he had done a poor job that day. But he turned up, and he was adequate.

Life Is Not What It Seems from the Outside

From the outside, we often look at the professional lives of others, and they seem so tidy. Everyone seems to know what they are doing, and it often looks like people are following a well-laid plan.

But life is rarely like that, even when you are a leading researcher. Physicists can become AI researchers, and engineers can find fulfillment in teaching. People move between research and academia all the time, and success can appear in many different ways.

Living through all of this, of course, feels very different.

There are uncomfortable decisions, missed opportunities, trade-offs, uncertain transitions, and ordinary days when the work feels far from exceptional. Few people (if any) have the luxury of not going through this.

The panelists offered no formula for eliminating that uncertainty. No such formula exists. We can all try to optimize our strategies, but ultimately, there is no optimal route to calculate a career in advance, no sequence of choices that eliminates uncertainty.

What matters is learning when to focus, when to commit, when to change direction, and when to accept that a decision only has to be right for now.

For young researchers looking ahead at decades of work, the panel had a liberating lesson. The next choice does not have to determine the rest of your life.

The post ­The Career Path Is Not a Straight Line (and That Is the Point) originally appeared on the HLFF SciLogs blog.