The goal of this project is patient-specific guidance of cancer treatments via Magnetic Resonance Imaging of tissue electrical conductivity.
In cancer tissues, the abnormal concentration of electrolytes (e.g. sodium) leads to altered tissue electrical conductivity with respect to the surrounding healthy tissues. Recent cancer treatment techniques rely on the use of low frequencies electrical conductivity for optimal guidance of the treatment modalities. Knowledge of subject-specific tissue electrical conductivity at low frequencies is therefore essential to maximize the efficacy of these treatments. However, non-invasive measurement techniques to assess tissue electrical conductivity at low frequencies are currently not available. Currently, tissue electrical conductivity can be estimated non-invasively with Magnetic Resonance Imaging (MRI) at high frequencies (hundreds MHz). By combining tissue conductivity measured at hundreds MHz with the water diffusion tensor, also measured with MRI, tissue conductivity at a low frequency range can be estimated.
In this project, you will first optimize MRI sequences used to measure high frequency conductivity. You will characterize their robustness, reproducibility, and repeatability on phantoms and in-vivo. You will develop a reconstruction framework (model / AI based) to map high frequency conductivity and to translate it to low frequency conductivity. You will assess in simulations how changes in high frequency conductivity translate to low frequency, as well as the needed sensitivity in high frequency conductivity measurements to optimally guide these cancer treatment methods. Therefore, this project will allow you to explore both experimental and computational components.
This research will be performed in close collaboration with a world-wide leading company in cancer treatment technology.
We offer a full-time (1.0 fte) PhD/Postdoc position. In addition, you will receive an year-end bonus of 8.3% and holiday allowance of 8%.
You will work within the Cancer Center and Imaging Division, and you will be embedded in the Computational Imaging Group.
Within our division, we provide high-quality patient care and research. In our team, we conduct internationally leading scientific research in the field of medical imaging techniques for cancer treatment guidance with the goal of implementing these techniques in patient care. You will work in a team of physicists, physicians and engineers together with academic and industrial partners. Several times a year there are social, educational and scientific events organized especially for you and fellow PhD students / Postdoc researchers. Also, you will be encouraged to attend international conferences with your colleagues, e.g. ISMRM.
We are looking for a highly motivated, enthusiastic candidate with interest in MR imaging, modeling & AI and electromagnetism.
If you are interested in this position, please respond to this vacancy with a motivation letter and your CV (including past experience, publication record, and at least two references). We look forward to hearing from you.
Depending on the type of position for which you are accepted, you will end up in salary scale 10 (PhD) (€ 3230 - € 5088) or salary scale 11 (Postdoc) (€ 4325 - € 5919).