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integrate data-driven, biologically informed modeling and machine learning for neural decoding, bridging fundamental discoveries with clinical applications in sensorimotor and cognitive function and
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emphasis on fMRI-based studies, network neuroscience, and the application of statistical machine learning and AI approaches to neuroimaging data. This includes developing research/project ideas
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, EEG/MEG, behavioural methods, computational modelling, automated neuroanatomical phenotyping, machine learning and advanced statistical approaches. The doctoral project will be developed jointly
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expertise to investigate individual differences (that might predict learning and outcomes), underlying cognitive and neurobiological mechanisms, and intervention outcomes using tools including, but not
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Mathjobs.org | 29 days ago
machine learning methodologies to address them. The search is broad and welcomes research spanning modern statistical methods, machine learning, AI, and emerging approaches to data science, with
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machine learning methodologies to address them. The search is broad and welcomes research spanning modern statistical methods, machine learning, AI, and emerging approaches to data science, with
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Cognitive Neuroscience Apply for this job See advertisement About the position Position as PhD Research Fellow in Machine Learning and Applied Cognitive Neuroscience available at the Department of
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, machine learning applications, and analyses of individual disease trajectories. Your tasks will include: Integrate multimodal neuroimaging datasets from MRI, PET, EEG, and fNIRS studies Characterize brain
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not required, we are particularly interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional
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/nl/medewerkers/s-e-verwer) for more information on possible research topics. Your profile Master’s degree in computer science, mathematics, machine learning, cybersecurity, or related field. If you