Work's Description

Motivation: Nuclear magnetic resonance (NMR) has become indispensable in various fields of research such as physics, chemistry and medicine. It provides a non-invasive and non-destructive method for examining a wide range of samples, for example to find out the composition of SARS-CoV-2 at an atomic level.
A homogeneous magnetic field is essential for an accurate and precise result, but this is – among other factors – altered by the sample to be examined. The magnetic field can be adjusted by so-called "shim coils", but this procedure must, in many times, be carried out manually and requires a lot of time and experience. This process is called "shimming".
AI has been introduced to enhance and speed up the tedious and time-consuming shimming process.

Your Tasks

Your tasks include (1) scaling existing AI-driven shimming algorithms to higher input and output dimensions. And (2), to explain the DL models’ predictions with XAI approaches, such as captum or SHAP values.
You will be part of Prof. Korvink’s research group where you can get support from members with expertise in NMR theory, methodology, hardware, and simulation.

Personal Qualifications,

• Highly motivated student with excellent academic record
• Excellent knowledge of programming languages (python)
• Experience with (explainable) AI and deep learning
• Optional: Basics in NMR
• Languages: English or German

ContractÄs Duration:  2 - 4 Months           Entry Date:  ASAP

Technical Contact