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connectivity and graph-theoretic analyses Familiarity with MR sequence programming (Siemens or GE platforms) Machine learning / AI applied to neuroimaging data EEG acquisition and analysis Use of neuroanatomical
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disorder. This project investigates early neural markers of psychosis by integrating multimodal neuroimaging with genetic and transcriptomic data and applying machine-learning approaches to identify
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) Experience with behavioural and neuroimaging (fMRI, M/EEG) data design/collection/analysis Experience in machine learning and AI A collaborative approach to doing science and willingness to help other lab
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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routine background checks. Essential Duties and Responsibilities Neuroimaging data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms
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medical education. http://www.med.upenn.edu/ . PennLINC Neuroimaging Research Coordinator (A/B) Ted Satterthwaite and the Penn Lifespan Informatics and Neuroimaging Center (www.pennlinc.io) are recruiting
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schools, doctoral supervision, and software outputs central to the Centre’s mission. About You You will have, or be close to completion of, a PhD/DPhil in Statistics, Machine Learning, Data Science, or a
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. Skills in computational modelling or machine learning applied to brain signals are an asset. We are looking for a highly motivated, rigorous and curious researcher who is ready to invest themselves in a
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | about 16 hours ago
for scientists in cognitive neuroimaging. The IDP further aims to establish a common vision between student and supervisor of the roadmap towards the successful PhD project, while at the same time minimising