
Nils Dienesch
Professorship for Computational Imaging
Research associates
Contact
Office hours
by appointment
Research field
My research focuses on accelerating MRI with deep learning using foundation models. In particular, I seek to develop a method that generalizes existing deep learning based MRI reconstruction methods, which currently focus predominantly on specific anatomical structures and imaging modalities. To achieve this I combine foundation models with zero-shot learning.
I offer supervision for projects, Bachelor’s theses, and Master’s theses to motivated students who have already gained first experience in the field of MRI reconstruction. Please note that applications will only be considered if submitted through the application form on our website.
- Since 10/2025
Ph.D. Candidate at the Computational Imaging Lab,
Friedrich-Alexander-University Erlangen-Nürnberg - 10/2021 – 08/2024
M.Sc. in Computer Science at the Friedrich-Alexander-University Erlangen-Nürnberg
Thesis: Zero-Shot Self-Supervised Deep Learning for MR Image Reconstruction - 10/2018 – 09/2021
B.Sc. in Computer Science at the Julius-Maximilian-University Würzburg
Thesis: Automated cardiomegaly detection through deep learning-based object detection
- Medizintechnik II Tafelübung (SoSe)
- Seminar: Machine Learning in MRI (WiSe/SoSe)