Multimodal Data (PET/MR/EEG) Analysis and Integration
Program Director UROP
- +49 241 80-90695
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- Project Offer-Number:
- UROP International
- Biomedical Engineering
- Organisation unit:
- Klinik für Psychiatrie, Psychotherapie und Psychosomatik
- Language Skills:
- Good proficiency in English
- Computer Skills:
- very good MATLAB or Python programming. Especially to handle signal/image/statistics/machine learning tools/packages processing (at-least two of these packages/tools).
- Please send a one page (max. 300 words) short motivation letter with research interests. A short proposal may also be added (not mandatory)
PET, MR and EEG provide complementary anatomical, physiological, metabolic, and functional information about the brain. Pooling information obtained with each modality has long been performed through parallel analysis of the sequentially acquired data and, more commonly today, by using software co-registration techniques. However, an off-line combination of data acquired separately with different imaging modalities is still insufficient, because several correlated patient-specific signals may vary over time. As a consequence, the full integration of different diagnostic modalities into a seamless clinical tool is mandatory for the acquisition of multi-parametric measurements on a routine basis in schizophrenia patients. By integration of three relevant modalities, it will facilitate multiparametric characterization of brain tissue in a single diagnostic session. Work place of research internship will be FZ Jülich.
Within the scope of ongoing study, summer research internship can be planned and adapted according to the student’s educational background and interests. One of the main outcomes of internship will be hands-on experience with MR, PET and EEG data acquisition and multimodal data processing.
Ideally, candidate should be a bachelor / master student in Biomedical Engineering, Information Technology (Machine learning), Psychology, (Cognitive) Neuroscience, Applied mathematics or related study programs. Basic knowledge about Medical Imaging/Medical Physics/Signal and Image processing. Proven programming (MATLAB or Python) and problem solving skills. Good knowledge about machine learning, statistics and ability to program algorithms using available MATLAB or Python based machine learning packages. Students who are pro-active and capable of independent work with good programming knowledge and have interest in science and research are only invited to apply.