Paula is 23 years old and a physics student at the University of Heidelberg. She has been working with us for a year as a working student in the NLP team. We asked her a few questions about her studies, her work here, and her path into IT.

1) You've been a working student in the NLP team for over a year now, but you're actually studying physics. What originally inspired you about physics and how did you get into IT from there?

What has always fascinated me about physics is the search for an even deeper understanding of the world. You are not satisfied with superficial explanations, but keep asking further. The aim is to understand phenomena from the ground up, starting from so-called first principles. This approach is what still inspires me today and can be transferred to many other areas. The transition into IT was an obvious choice for me. Machine learning is also a branch of physics. For instance, last year, the Nobel Prize in Physics was awarded to researches who have worked on machine learning. I applied for a working student position at Aristech in order to compensate the lack of practical programming experience in my studies. In my degree, I am specializing in this area, however, the focus predominantly on lies on the theoretical backgrounds there.

2) What makes you notice the differences between the field you are working in and the discipline you are studying? What are the challenges and are there also advantages that you think your degree brings with it?

For me, working in a discipline that is different from the one I am studying brings both advantages and challenges. One of the main challenges so far has been the field of linguistics, which I have had very little contact with before working here. I have also never worked on such a large software project before, which has brought a lot of new experiences with it. But that is not a problem, since I have been trained well by my great colleagues here and receive support whenever I need it.

Apart from the field of machine learning, I can only rarely apply specific content from my physics degree directly. However, a physics degree mainly trains systematic problem solving and promotes a certain tolerance for frustration. These skills help me when I have to get to grips with new and challenging tasks. It is also often very practical to look at things from a different perspective.

**3) What do you particularly like about project-related work in an interdisciplinary tech team? **

I really enjoy working in a large team on a joint project. At university, that rarely happens and you tend to work on smaller, isolated projects. Here, we work on a large project that you want to advance together, week after week.

I think it is great that people from many different areas get a chance here and the various professional or educational backgrounds are seen as something valuable. This makes working together very so enjoyable.

**4) What are you currently working on at Aristech? **

I am working in the NLP department and am currently occupied with the development of the NLP server. I test and implent new features, here.

**5) How does working here complement what you are learning at university? **

Working here mainly provides me with practical experiences, which I do not really get at university, as it is focussed more on the theoretical parts. This is the reason why I view my job here as a really valuable and practical addition to studying at university.

Being an active part of the projects, I learn a lot about practical programming applications und working in a project-oriented way. My colleagues also give me a deep insight into the tools all developers should be able to master. This knowledge will be really helpful for me later in my career, but also already during my advanced studies in research groups, or similar areas.

Note: If you would also like to gain your first professional experience and acquitre practical experience in addition to your degree, please send as an initiative application via [email protected]