Already while completing my bachelor's degree studies in chemistry, I felt drawn to theoretical topics such as simulations. Thus, choosing a master's degree program which focuses on these was a natural
consequence, and the CSiS program was the perfect candidate due to its four central topics: computer science, computer simulation with a focus on parallelization, numerical methods and a specialization to connect all of them.
The classes and their lecturers were as diverse as the program suggests. Many lecturers have a background in physics which might grant a new way of thinking depending on one's own. Most lecturers were always willing to help, and some even offered additional courses to provide further insight into their topics. Prof. Knechtli, the head of the program, puts an immense amount of effort into improving the program and is always open to feedback.
To get the most out of the program, though, I recommend having a basic understanding of programming and mathematics beforehand; a block course at the beginning of the program will help with the latter. In my thesis supervised by Prof. Jensen, I implemented a method that calculates Stark coefficients for Renner molecules using perturbation theory, i.e., simulates the effect of electric fields on their IR spectra. After treating the field-free case relatively cheaply by applying group theory, my method approximates this effect with almost no additional cost. To this end, I combined techniques from theoretical chemistry, linear algebra, computer science and parallelization, most of which were taught throughout the program. Afterward, I decided to delve more into numerical linear algebra and have since started a doctorate in applied computer science with Prof. Frommer and Dr. Kahl. In my research, I investigate a new way to calculate matrix functions acting on vectors. It is interesting to see how often I can use the knowledge that I acquired during this program.