International Max Planck Research School on Neuroscience of Communication: Function, Structure and Plasticity (IMPRS NeuroCom)
Module IV Neuroimaging Physics and Signal Processing
Projects in this module typically focus on the physical principles of modern neuroimaging techniques including RF technology, image processing strategies, and EEG/MEG source analysis, on biophysical tissue properties and their relation to microstructure and function, as well as on computational neuroscience and modelling of cortical networks. Experimentally, these efforts are supported through access to cutting-edge imaging technology, including a state-of-the-art 7T whole-body MRI scanner, a 3T scanner with 300mT/m high-performance gradients or a 306-channel MEG system.
Candidates should have a very good master's degree, preferably in physics or, alternatively, in physical chemistry, computer sciences, biomedical or electrical engineering or a similar degree of equivalent academic level. A genuine interest in developing novel biomedical imaging or neuromodeling should motivate your application. Good programming skills, preferably with experience in MATLAB, C++ or Python, are essential.
One main research topic of our department is (neuro-inspired) signal processing for all kinds of applications. This includes especially all applications directly related to a more or less direct information exchange via different types of sensors and actuators with the nervous system (BCI, biofeedback etc.).
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Our research topic concerns the investigation of electronic properties of solids with magnetic resonance. We use and advance magnetic resonance techniques to obtain unique insight into the electronic and chemical structure of materials including host-guest interactions.
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My research focuses on medical visualization and data analysis: The goal is to make use of all available data to guide reasoning and understanding of the information that is contained inside the data.
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biophysical modelling of EEG and MEG | computational modelling of neural networks | reconstruction of fiber connections with diffusion MRI, diffusion tractography, connectivity-based parcellation
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My research focuses on the use of magnetoencephalography in cognitive neuroscience with special focus on language processing. Consequently, I am interested in all methodological developments which improve the localization of brain activity in both respects spatial accuracy and temporal evolution.
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Our group is engaged in the development of methods for magnetic resonance imaging (MRI) and spectroscopy (MRS) including pulse sequences, RF hardware and image processing.
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Experimental techniques such as high-resolution, multi-contrast MRI, 4D light-sheet microscopy, or single-cell sequencing provide unprecedented, unique insights into life's inner workings across scales.more
My research group addresses visual data analysis which includes mathematical data analysis, scientific visualization, information visualization and visual analytics.
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Our vision is to develop and apply functional microstructure imaging and in-vivo histology using magnetic resonance imaging (MRI) as novel non-invasive MRI methods to reliably characterize the detailed functional and anatomical microstructure of the human brain.
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