As part of the collaboration between the Carinthia University of Applied Sciences (CUAS) and the Medical University of Vienna, seven PhD positions will be established with research starting in the 2023/24 winter semester. As we have announced previously Günther Grabner from CUAS and Wolfgang Bogner from MUV received an FWF doc.funds project, entitled: “Interdisciplinary platform for new research methods in the field of demyelinating diseases and brain tumours – where ultrahigh field MRI, histology, and artificial intelligence meet”.
The goal of this project is to bridge the gap between brain research and clinical needs with cutting-edge magnetic resonance imaging (MRI) and machine learning. It will combine scientific expertise and equipment at the cutting edge of technology from three departments of the Medical University of Vienna – the University Hospitals for Radiology and Nuclear Medicine, for Neurology as well as for Neurosurgery – and CUAS in the study area Engineering & IT, Medical Engineering and Analytics.
Four of the PhD candidates will be situated in Klagenfurt, at the CUAS, and three in Vienna, at the MUV. The positions are open for 3.5 years. All 7 PhD candidates will be enrolled in the N094 Medical Imaging PhD program of the MUV, with some lectures held at the CUAS. To meet the highest international standards, the PhD candidates will be encouraged to go for a research stay at one of our seven internationally renowned partners (including e.g. Harvard, MIT and industry partner ICOMETRIX).
Reducing static magnetic field inhomogeneities in the human brain
The goal is to develop a technology to mitigate undesirable local/temporal errors in the magnetic field(B0) of MR scanners, which would cause degraded MRI data quality. These limitations will be overcome by combining custom-made MR hardware with deep-learning-based software, which—when integrated on the MR scanner—will enable real-time mitigation of B0-field errors. This thesis will involve MR scanner programming, developing deep neuronal networks and experimental validation in phantoms/healthy humans. For more info and to apply, click here.
Developing metabolic MR imaging techniques for neurological disorders
This FWF-funded project has the goal to optimize new metabolic imaging techniques termed Chemical Exchange Saturation Transfer (CEST) for clinical application in patients with demyelinating disorders such as Multiple Sclerosis and brain tumours. The diagnostic and prognostic information obtained by this technique will then be compared to our established MRI techniques to perform a preliminary evaluation of the clinical value and complementarity of CEST and similar magnetization transfer techniques. This thesis will involve MR method optimization, data acquisition/evaluation, and analysis of multi-parametric MRI data obtained at our 7T MR scanner in phantoms, healthy volunteers and patients. For more info and to apply, click here.
Prediction of Histological Features based on in-vivo MRI
Magnetic resonance imaging is sensitive to iron content and myelination, but the exact relationship between these tissue properties and MRI images is unclear. Both biological tissue parameters are needed to study the development and diseases of the human brain but are currently only accessible via ex vivo histology. This PhD project will focus on the development of deep learning-based techniques to predict ex-vivo histological features based on in-vivo MRI e.g. to visualize myelin and iron distributions. For more info and to apply, click here.
Classification of MS Lesions in Iron and non-Iron Lesions using Deep Learning
The reliable detection and accurate monitoring and tracking of multiple sclerosis lesions are critical for disease course assessment. This PhD project will focus on the classification and further analyses (rim expansion, T1 black holes, atrophy) of the lesions in 7T MRI images using deep learning-based techniques. For more info and to apply, click here.
New MRI biomarker development
Iron accumulation at lesion indicating chronic smoldering brain inflammation is becoming integral in the understanding of progressive demyelinating diseases. This rim-like iron accumulation can be detected in vivo using 7T MRI. However, another demyelinating disease, X-linked adrenoleukodystrophy (X-ALD), also shows profound iron accumulation at inflammatory lesion rims. Here, we would like to evaluate the added value of 7T iron imaging compared to 3T MRI in the detection of smoldering inflammation in X-ALD, with the goal of sensitively detecting inflammation. For more info and to apply, click here.
Precise preoperative characterization of brain tumors
The primary aim of this PhD position is the precise preoperative characterization of different brain tumors with 7 Tesla MRI and MRSI. Radiomics and genomics/proteomics features derived from clinical sampling will improve the precision of preoperative brain tumor characterization. These prospective tasks include the recruitment of study patients, transfer of images to neuronavigation, support in intraoperative data and tissue collection, evaluation of histological analyses, follow-up examinations and comparisons of clinical MRSI to other imaging methods such as intraoperative 5-ALA fluorescence. For more info and to apply, click here.
Augmented Reality meets Neuro Surgery
This PhD project is situated in the field of pre-operative neurosurgical planning using Augmented/Virtual Reality with the focus on adaptive visualization and efficient 3D user-interfaces. On the basis of medical imaging data (e.g., MRI), a prototype environment for head-mounted displays shall be created that is focused on adaptive visualization and spatial interaction. This will support experts in preparing efficiently for medical interventions by providing intuitive tools for visualization, editing and documentation. For more info and to apply, click here.
Application submission deadline: 30.04.2023 CET
Online interview days: 22-24.05.2023
MedTech @ FH Kärnten