Krems an der Donau, Lower Austria, Austria
I won’t try to impress anyone with a long essay about “changing the world.” Instead, here’s a straightforward overview of who I am and how I work. Why research? Because I don’t enjoy having nothing to think about. I thrive on solving problems, following ideas into deep rabbit holes, and understanding how things work. And of course, there’s something genuinely rewarding about contributing—however modestly—to expanding our understanding of the world and improving how we operate within it. How I work: I value quality over quantity, especially in research. I don’t like delivering work that’s thin on substance, and I avoid making claims that aren’t well-supported by actual results. Yes, this means I sometimes move slower than others—but I’d rather contribute one solid piece of work than ten papers that add little to the field. I’m a bit of a perfectionist, at least until further refinement yields diminishing returns. At that point, I aim for a robust, functional model rather than chasing endless optimizations. Related to that, I sometimes get hyper-fixated—whether that means ruminating over a paper for hours or getting lost in Wikipedia trails—but the end result is usually a thorough, well-reasoned answer. I’m also someone who notices inefficiencies, whether in code, workflows, or lab routines. When something stalls progress, I feel compelled to change and improve it. The upside of all this is that once the dust settles, I tend to deliver results that are well-understood, dependable, and efficient. On a more personal note: I enjoy being around curious, driven people who like questioning existing and even prevalent assumptions and refining ideas. Environments like that bring about the best work. I’m fairly extroverted, I enjoy talking to people, and I don’t function well in long stretches of isolation. Outside of research and social life, I stay active through a variety mountain sports—skiing, hiking, climbing—and, when the weather isn’t cooperating, the gym. And when I need a slower day, you’ll find me cooking, reading, or playing video games. If you’re curious about my work or can imagine collaborating, feel free to reach out.
I completed my practical university term at Linköping University in the Department of Biomedical Engineering (IMT), working in a systems and computational biology group. This is the first internship I landed through a research pitch of my own, which quickly evolved into a project using Boolean gene regulatory network (GRN) modelling to explore how healthy pancreatic ductal epithelium transitions toward PDAC at the transcriptional level, and how targeted gene knockouts might influence that process. While the overall methodology builds on established approaches in the field, I chose to reimplement the full pipeline in Python to really understand each step and its underlying logic. From preprocessing and data cleaning to cell-type annotation, CNV calling, pseudotime and phylogenetic analysis, and finally Boolean model inference and simulation, I’ve been working through the entire workflow myself. It’s been a steep learning curve, but one that gave me a pretty solid grasp of why each analysis step exists and how they connect. Because the dataset is large and some steps get computationally heavy, I also had to get comfortable working on an HPC cluster and adapting my scripts to run efficiently there.
During my summer internship at Bisy, I had the opportunity to put the lab skills from my first university terms into practice in an actual wet-lab environment. I worked on a project aimed at optimizing protein expression in K. phaffii, using a range of standard molecular biology techniques—PCR, gel electrophoresis, protein quantification, along with more project specific methods I learned on the job. My work focused on generating data to help move the project forward, and by the end of the internship we did manage to achieve an improvement in the overall expression levels. While the project itself wasn’t my own design, I worked largely independently after the initial two-week introduction. I also took part in regular team meetings although more as a spectator, which gave me a good look at how progress is discussed, planned, and adjusted in a biotech setting. Overall, the internship was an important step in translating theory into hands-on lab work and gave me a clear sense of how research projects operate in the biotech industry day-to-day.
During my one-week internship at Canon Medical Systems Europe, I had the chance to work alongside an experienced ultrasound technician and get hands-on with the practical side of medical equipment. We handled routine maintenance on externally owned ultrasound machines, and I helped troubleshoot software issues and reconfigure the systems so they were ready for reliable use by customers. It was a very practical, problem-focused experience that taught me how important quick, careful decision-making is when working with medical devices. Besides the technical work, I also supported the day-to-day running of the office—coordinating customer visits and helping the service team stay organized so they could respond efficiently. This gave me a good look at how a service-oriented technical team actually functions behind the scenes. The internship gave me a solid understanding of medical equipment maintenance and the realities of customer-focused technical support. While my long-term goal is to move into basic research, this experience broadened my view of the healthcare technology landscape and showed me how precision and reliability on the side of application tie everything together.