Vacancy No. IMT 34-2023

IMT 34-2023 Internship: Artificial Intelligence for nuclear magnetic resonance applications – Shimming algorithms and explainable AI

Job 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 task: 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 qualification

Field of Study: Computer Science/Engineering, Mathematics, Information technology or similar

  • 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
Organizational unit

Institute of Microstructure Technology (IMT)

Starting date

as soon as possible

Contract duration

2-4 Months

Contact person in line-management

For further information, please contact Moritz Becker, e-mail: moritz.becker@kit.edu or Mazin Jouda, phone +49 721 608-23150.

Application

Please apply online using the button below for this vacancy number IMT 34-2023.
Personnel support is provided by 

Ms Carrasco Sanchez
phone: +49 721 608-42016,

Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany

Recognized severely disabled persons will be preferred if they are equally qualified.