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model of human working memory. During the project, we will follow an intertwined model-experimental approach. First, we will use electroencephalography (EEG) experiments to investigate the neural basis
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 3 days ago
processing and will involve EEG and MRI experiments as well as realistic modeling of biological neural networks. It is a cooperation between the TU Berlin, the TU Chemnitz, the Czech Academy of Sciences, and
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in advanced methods for the analysis and classification of EEG and auditory signals. The group of the project is multidisciplinary, with experts in signal processing, machine learning, acoustics and
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research environment with access to a wide range of neuroimaging techniques (EEG, MEG, fMRI). More information about the BCBL can be found at: https://www.bcbl.eu/en . Where to apply Website https
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will perform research on foreign-accented speech processing. Research methods include behavioural measures and electroencephalography (EEG), optionally eye-tracking. The Doctoral Candidate (DC) will be
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plan to investigate brain reorganization underlying visuo-cognitive mechanisms through functional neuroimaging techniques such as fMRI and EEG. This project has major implications for health and well
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environment, with access to state-of-the art brain imaging facilities (two research-dedicated MRI scanners / 1.5 and 3T, hybrid PET-3T MRI, MEG-EEG). The vibrant research community at CRNL and other nearby
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research projects (e.g., data collection, analysis) Experience with MEG or EEG data analysis. Knowledge of Basque, Spanish or LSE (or willingness to learn) is a plus LanguagesENGLISHLevelExcellent Additional
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analyses using your own data and large public data resources and integrate your findings with clinical data (symptoms, EEG, etc). Finally, you will contribute to other activities of the STXBP1 team
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electroencephalogram (EEG) and potentially other modalities (e.g., functional near-infrared spectroscopy (fNIRS)) to improve decoding accuracy and user-specific adaptation. Key research areas include: EEG signal