18-2020-IMT PhD Position on AI-assisted NMR magnet shimming
Institute of Microstructure Technology (IMT)
Nuclear magnetic resonance (NMR) is an invaluable tool that is widely used in different branches of science such as biology, chemistry, physics and medicine. It is also a very versatile method, which includes both spectroscopy and imaging. The homogeneity of the static magnetic field is essential to obtain a high quality NMR spectrum or image. One of the solutions to this problem that is being used in order to make the magnetic field of a high-field NMR magnet homogeneous over the sample to a highest possible degree is to use additional coils named "shim coils". Currents that are passing through shim coils help to homogenize the magnetic field by compensating its gradients. One of the challenges of NMR measurements is correct and fast shimming of the magnet. This process requires a lot of time and experience from the person performing NMR measurements.
The goal of this project is to solve the problem of NMR magnet shimming by automating the process. To resolve this challenge a suitable machine learning (ML) algorithm is expected to be developed that can achieve the desired result. ML is not only capable of solving tasks without cumbersome calculations and does not require huge computer resources, but also can analyze the incoming information independently of the person and much faster than them.
as soon as possible
- M.Sc. in Computer science, Electrical engineering, Mechanical Engineering, Chemistry, Physics or equivalent
- Experience with machine learning, programming (Python), preferably with previous experience in developing ML algorithms
- Experience with NMR spectroscopy appreciated, but not expected
limited to 3 years
Application up to
Contact person in line-management
For further information, please contact Dr. Mazin Jouda, e-mail firstname.lastname@example.org
Please apply online using the button below for this vacancy number 18-2020.
If qualified, severely disabled persons will be preferred.
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Phone: +49 721 608-25010,
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