Collaboration, computation, culture: Jacob Schreiber's year at the IMP
Jacob Schreiber is a computational scientist that uses machine learning to understand gene regulation across the genome. He joined the IMP in 2024 for a one-year stay as a visiting scientist before starting his faculty position in the United States. During his time in Vienna, he worked on developing computational tools to make machine learning more accessible to experimental biologists. Now leading his own research group, he reflects on his experience at the IMP, the value of its collaborative environment, and how he sees the future of AI and synthetic biology taking shape in Europe.
What brought you to the IMP for your one-year stay as a visiting scientist, and what were your goals during that time?
I came to the IMP for a year before starting my faculty position in the US, with a few clear goals in mind. Scientifically, I knew that the research being done at the institute was outstanding, and I wanted to immerse myself in that environment—to learn how top scientists in Europe operate, how they approach questions, and how they navigate challenges. In a way, it was a chance to observe and learn from successful group leaders so that I could become a better PI myself later on. Another key goal was to build collaborations across Europe. Being based at the IMP made that much easier: I could connect with researchers across Germany, Norway, and England—people I likely wouldn’t have met had I stayed in the US. So overall, my time there was about making connections and absorbing as much as I could from the IMP’s unique scientific ecosystem, with the hope of carrying some of that spirit and culture back with me.
How would you describe your experience during your time at the IMP?
It was quite different from what I’d experienced before. I came up through large university systems in the US—the Department of Computer Science at the University of Washington alone has over sixty faculty members, and Stanford, where I did my postdoc, is also a huge place. In those environments, collaborations often happen around a single project or two, and then people move on. At the IMP, it felt much more personal and sustained. The institute is smaller, so you get to know people closely, and collaborations can develop naturally across many projects because everyone’s just down the hall.
I was also the only person doing the kind of computational genomics work that I do, which was both challenging and motivating. It pushed me to get organised quickly, but it also meant that when I did, there were plenty of exciting opportunities to connect with others. Some of my most rewarding interactions came from that proximity.
What do you think makes the Vienna BioCenter stand out as a research environment?
One of the things that immediately stands out is how closely connected everyone is, both within the IMP and across campus. Having different institutes like the IMP and IMBA side by side makes spontaneous interactions much easier. Simply seeing people over lunch or passing them in the hallway often sparks new ideas or even collaborations. I remember being told by a graduate student that PIs are always busy, and at the time I thought, “Sure, everyone’s busy.” But now, as a PI myself, I really understand that there’s never enough time for everything you’d like to do. At the Vienna BioCenter, though, that proximity makes a huge difference, sometimes a project can start just because you bump into someone you’ve been meaning to talk to.
Beyond that, what really sets the Vienna BioCenter apart is the quality of the people. Everyone here is genuinely excellent in their field. You see it not only in their publications but also in how the institute is regarded externally. When I visited other places in Europe, people immediately knew about the IMP and spoke of it with real admiration. That kind of reputation, built on both excellence and collaboration, is rare and well deserved.
What were your main research goals during your year at the IMP?
Since I was there for only a year and didn’t have students of my own, I set more focused goals than a typical PI might. My field is computational genomics, essentially using machine learning to understand the genome, and one of the key challenges in this area isn’t so much scientific as it is engineering related. Researchers with a computational background can build and apply these models, but for many experimental scientists they’re not yet accessible. My aim was to change that. I wanted to make machine learning tools as easy to use as any standard lab software, something that any scientist could adopt without needing to know all the technical details. During my time at the IMP, I refined these tools by testing them myself and getting feedback from students and collaborators, figuring out what worked in practice and what didn’t.
Was there a particular collaboration or project that stood out for you?
Yes—one that really captured the spirit of what I was trying to do was a collaboration with Moritz Gaidt’s group. One of his students, Luisa, had spent over a year running experiments to characterise a biological process. Using the tools I’d developed, we were able to reproduce her findings computationally in about a week, and the results aligned perfectly. It was an exciting moment for everyone involved. For me, it was proof that the tools could genuinely empower experimental biologists to explore data in new ways. Seeing Luisa use them independently afterward was particularly gratifying. By the end of my stay, three of these projects had turned into publications, which made the year feel both productive and meaningful.
Before coming to the IMP, I had thought carefully about how to make the most of a single year. Focusing on engineering and tool-building made sense, it was a tangible goal that could have a real impact. What made this possible was the freedom the IMP gave me: I didn’t have to worry about administrative responsibilities or grant applications, so I could fully focus on the science itself. That level of freedom is rare, and it allowed me to accomplish far more in a short time than I could have elsewhere.
Synthetic biology and AI are transforming the way we do research across fields, especially in biology. How do you see the Vienna BioCenter positioning itself in this rapidly evolving landscape?
AI and computational approaches are clearly becoming integral to biological research, and I think the Vienna BioCenter has recognized that early on. Alex Stark’s group, for instance, is doing fantastic work on the computational side, and the establishment of the AITHYRA Institute is a very exciting step. Focusing explicitly on artificial intelligence as a pillar of research is absolutely the right direction to take. The scientists being brought in AITHYRA, particularly the new group leaders joining the institute, are doing ambitious and forward-looking work.
I think Europe has an incredible talent base and research culture, but the scene can sometimes move at a slower pace compared to the US. Initiatives like AITHYRA are exactly what’s needed. If Europe builds on this momentum, I believe it can play a major role in shaping the future of AI and synthetic biology.
What aspects of Vienna or the IMP do you miss the most now that you’re back in the US?
Spending a year at the IMP meant building close connections with so many people, and I definitely miss that. I still keep in regular contact with many of them. One thing that stood out for me was the honesty in feedback, because everyone was so tight-knit and welcoming, it was easy to get straightforward critiques. It can be tough to hear the weaknesses in an approach, but that openness ultimately allowed everyone to do their best work. I also really appreciated the culture around events and presentations. Attendance at seminars and the weekly research reports was consistently high. That level of engagement creates a virtuous cycle: researchers put more effort into their presentations, people show up to see the work, and it becomes a genuine celebration of the science being done. I found that both motivating and inspiring, and it’s something I really miss about being part of that community.
Further reading
Jacob Schreiber’s website - https://jmschrei.github.io/
Jacob Schreiber on Twitter (X)