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a Ph.D. in a relevant area (psychology, cognition and neuroscience, neuroscience)and have research experience relevant to analyzing MRI-based datasets (task-based fMRI, rsFC, DTI, structural MRI
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Metabolic MRI at 7 T with Genomics for Improved Characterization of Grade 2/3 IDH-wildtype Astrocytoma ("Molecular Glioblastoma")” Project Description https://www.ncn.gov.pl/sites/default/files/listy
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of fMRI data in task-based and resting- state tasks, including preprocessing, GLM modeling and BOLD contrast analysis, as well as functional and brain network analysis, • Experience in structural MRI data
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will support a multidisciplinary research program investigating glymphatic modulation through neuromodulation, neuroimaging, and neurophysiological monitoring. The position will lead and assist with MRI
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, neuroscientific, or closely related discipline Demonstrated background and hands-on experience in the analysis of longitudinal neuroimaging data (e.g., structural MRI, diffusion imaging) from large, multisite
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: Develop and implement advanced AI and computational neuroscience models for brain structure and function. Lead modeling efforts for multimodal brain foundation models. Work with fMRI, structural MRI
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applications, including diabetes, obesity and metabolism. The primary funded project examines changes in the dopaminergic system in the pancreas and brain during diabetes using PET/CT and MRI. Several additional
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such as flow cytometry, confocal microscopy, MRI/PET imaging and bioinformatics tools. Work with team members across different disciplines such as chemistry, biology, neurosurgery, and engineering. Write up
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data analysis (e.g., MRI preprocessing, statistical modeling, familiarity with tools such as FSL, SPM, AFNI, or similar platforms). Proficiency in statistical programming (e.g., R, Python, MATLAB
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• Perform experiments to evaluate the biodistribution and efficacy/safety of nanoparticle formulations. • Interpret data with advanced methods such as flow cytometry, confocal microscopy, MRI/PET imaging