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for injection of chemical and viral vectors, and for implantation of multiple stimulation and recording electrodes. Designs, executes, and analyzes research studies using intracranial EEG data from animals
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network, translate scalp to intracranial EEG data, and most importantly rank the surgical target and predict the recovery brain resection outcome. Patient demands and rapid establishment of new
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or more of the following techniques: Electroencephalography (EEG) Functional Near-Infrared Spectroscopy (fNIRS) Biosensors (ECG, GSR…) Start Date and Conditions Start date: April-May 2026 in Barcelona
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ability to write clean, well-documented analysis code. Ability to work with EEG data and apply multivariate methods to extract meaningful measures relevant to memory and consolidation. Skilled in developing
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spearhead technical development, data analysis, and publication efforts for a student-led initiative using OpenBCI hardware, EEG recordings, eye-tracking integration, and machine learning to enhance neural
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. The post holder will have the opportunity to be involved in cutting-edge bespoke neuroimaging technology [3T/7TfMRI-EEG fusion] and advanced data analytics to uncover and predict patterns in large multimodal
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, neuroengineering, Psychiatry, or related field. Experience with population statistical techniques, EEG/ERP analysis, hardware development, and cognitive neuroscience. Baylor College of Medicine is an Equal
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also be opportunities to contribute to additional projects, such as projects utilizing intracranial electrical stimulation and intracranial EEG (iEEG) data, depending on the candidate’s interests and
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postdoc associate. The individual will implement, simulate and analyze models of epileptic source localization from EEG signals. Collaborate with clinicians to obtain and analyze imaging, EEG, and outcome
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project that links processing speed measures to previously acquired functional and structural MRI data. The project will also involve simultaneously acquired and co-registered fMRI and EEG measurements