7 July 2026
For Touska, the scholarship first and foremost meant financial peace of mind. Without having to worry about tuition fees and the cost of living in Amsterdam, she could fully focus on lectures, projects and research. The fellowship also offered mentoring by experienced AI engineers at Qualcomm, giving her concrete advice on research ideas, career choices and working in the tech sector.
From the very first semester, Touska immersed herself in the mathematics behind machine learning, probabilistic models and modern AI architectures such as transformers. The fellowship also opened new doors. Through the UvA and its network, Touska was able in her second year to carry out a research project at ASML, where she worked on applications of AI for lithography metrology: the ultra‑precise measurement of patterns on semiconductor wafers.
This project developed into her Master’s thesis, which has since been accepted for presentation at the International Conference on Learning Representations in Brazil, a leading conference in the field of machine learning. For Touska, the Master’s is only the beginning. She dreams of a career in which she combines cutting‑edge AI research with real‑world impact, as a researcher, machine‑learning engineer or AI developer. She wants to continue working on models that are not only powerful, but also reliable, transparent and beneficial to society.
The Amsterdam unit of the European ELLIS Society is very pleased with the opportunities created by the Qualcomm scholarship. This local networking and research centre brings top talent and partners in the region together to promote excellent research and breakthroughs in artificial intelligence and machine learning.
Jan‑Willem van de Meent, Director of ELLIS Amsterdam and Associate Professor at the UvA, explains: 'Partnerships such as these between Qualcomm Technologies, the Master’s programme in Artificial Intelligence, the UvA Fund and the ELLIS Unit Amsterdam make trajectories like Touska’s possible. They give students the financial scope to concentrate fully on their studies, combined with direct exposure to research in industry.'