PhD in Robust and Efficient AI for NMR Spectroscopy and Drug Screening Karlsruher Institut für Technologie in Germany

PhD position at Karlsruher Institut für Technologie (KIT) in the junior research group Robust and Efficient AI at the Scientific Computing Center (SCC).

The project is part of the Collaborative Research Center CRC 1527 HyPERiON and focuses on robust and efficient AI, deep learning, high-performance computing (HPC), and NMR spectroscopy for drug discovery. The research aims to resolve signal overlap in parallel NMR spectroscopy by developing transformer-based neural networks that can generate individual, decoupled spectra from coupled spectra.

You will work on scalable AI methods for the natural sciences, including dataset creation from existing CRC experiments and your own experiments during a research stay at KIT’s Institute of Microstructure Technology (IMT). The project also includes self-supervised pretraining, masked sequence modeling, task-specific fine-tuning, and analysis of whether the model learns underlying physical principles of nuclear magnetic resonance.

Eligibility highlights: MSc in computer science, physics, mathematics, or an equivalent discipline; strong programming/software development skills, preferably in Python; prior experience with deep learning model development/training or NMR methods is preferred.

Funding: paid position, salary category 13 TV-L, 75% part-time, gross annual salary EUR 43,200 to 46,400. Contract runs until 2030-06-30.

Application deadline: 2026-07-23.

How to apply: use the KIT application portal linked in the posting and submit before the deadline. For general application questions, contact Dominik Meschar at KIT.