PhD position Untangling multi-property NMR signals in drug screening with data-driven neural net...

Area of research:

Other

Part-Time Suitability:

The position is suitable for part-time employment.

Starting date:

Job description:

Within the Collaborative Research Center (SFB) HyPERiON at KIT, an innovative PhD project is offered that focuses on resolving signal overlap in parallel NMR spectroscopy using artificial intelligence (AI). NMR spectroscopy is a key tool in drug discovery. However, in a parallel setup, signal couplings and overlaps occur that make it difficult to extract critical molecular information. The aim of the project is to develop AI models capable of generating individual, decoupled spectra from coupled NMR spectra.

Within the scope of the project, your responsibilities will include:

• Developing a transformer-based neural network for the processing of NMR spectra
• Creating datasets from existing experiments within the CRC and from your own experiments, which are to be carried out during a research stay at KIT’s Institute of Microstructure Technology (IMT)
• Applying self-supervised pretraining based on masked sequence modeling and task‑specific fine‑tuning to the trained neural network
• Analyzing the extent to which the developed model can learn the underlying physical principles of nuclear magnetic resonance

You will further be part of HyPERiON, participating in CRC activities and engage with the other PhD students and projects.

Key Focus Areas

• Scalable deep learning methods for nuclear magnetic resonance
• Self-supervised pre-training techniques and transfer learning approaches in Transformer‑based architectures
• GPU‑based computing and high‑performance computing (HPC)
• Application of AI methods in a scientific context