Prof. Dr Christina Kratsch: A headhunter from HTW Berlin approached me. I had actually had no intention of returning to the academic system after my doctorate. However, the recruiter aroused my curiosity and got me thinking about the University of Applied Sciences (UAS) as an institution. As the graduate of a traditional university I honestly had no real idea of what a UAS was. In discussions with the appointments committee, I realised that the expectations were very high - not only did the post involve a lot of teaching, but also research and involvement in academic self-administration; in my case, I was also asked to show particular commitment to a specific AI project. However, I also got the impression that I would have the freedom to set my own priorities. In the end, that was the deciding factor in my decision to accept the professorship. I later thanked the headhunter personally for approaching me. Being contacted by her was one of the best moments in my professional career.

The unique combination of research and practice. Yes, I do less research than I’m used to from traditional universities; I don’t write paper after paper and I’m far from generating revolutionary waves academically. But I am still close to the current topics of artificial intelligence (AI), because I integrate them into my teaching in the form of company-related projects; the structure of our degree programme makes this possible. This is a form of research that suits me well, because I not only reflect on the use of AI in companies in theory, but also test it in practice and can thus drive it forward. I know from my own experience what makes companies tick and what they need. So it fits together perfectly.

Initially, I found the thought of such a high teaching load pretty daunting. 18 hours of teaching per week, i.e. 18 weekly study hours, is quite a lot and can be off-putting. But that may be due to a false image of teaching. Our degree programme is very project-oriented. So I’m not standing in a seminar room for 18 hours lecturing to students. Instead, I work on exciting research and development projects together with the students, exchange ideas with researchers and entrepreneurs and can be innovative in terms of my methodological approaches. And still have time for theory, have the opportunity to attend interesting lectures, etc.

Fairly unusually, I started teaching mid-way through a semester, a kind of speed start. But my colleagues were kind enough to accommodate me, take me along to their courses and help with the organisation. That was amazingly helpful. However, I did have to design one course from scratch; back then I often didn’t know on Monday what I would be talking about on Tuesday. But there’s nothing wrong with a little challenge now and again!  In essence, I was used to speaking as a data science consultant and have always enjoyed giving talks and organising workshops. So from a didactic point of view, I was already familiar with the methodology.

To be quite honest, it’s much more important than I expected. The exchange with students is incredibly enriching. I like it when they scrutinise things critically, make progress in terms of content and experience personal and academic success. It’s also really fun to pave the way for the next generation of academics as they enter their professions and thereby introduce state-of-the-art AI into companies.

That actually plays a major role. All my colleagues are very dedicated and enthusiastic, there is always a spirit of optimism here. We are constantly developing the AI workshop at HTW Berlin, for instance. This is a place where we teach, research and work together to apply AI technologies to current industry problems together. There, we forge many important connections with companies.

We also recently established our new Master’s degree programme with an “Applied Research” track; this is a completely project-based degree programme in which students work on a large research project and complete relevant modules.

Let’s put it this way: in terms of hours, I probably don’t work any less than I used to when I worked in industry. But because I am completely free to set the priorities in terms of content and organise my time, working is easier and, above all, much more fun.