POSTDOCTORAL FELLOWSHIP IN COMPUTATIONAL MODELING OF BRAIN NETWORKS   Currently Available: The Stanford Cognitive and Systems Neuroscience Laboratory invites applications for a postdoctoral fellowship in computational modeling of human brain imaging data using deep neural networks. The successful candidate will be involved in a multidisciplinary project that seeks to develop novel computational frameworks for robust identification of neurobiological signatures of psychiatric and neurological disorders combining deep learning and convolution networks and dynamic brain circuit analyses with task and resting-state fMRI. Clinical disorders currently under investigation include autism, ADHD, anxiety and mood disorders, learning disabilities, schizophrenia, and Parkinson’s disease. We seek talented and highly-motivated individuals with a strong background in at least one of these areas: deep learning algorithms and optimization (theory and practical implementations); computational modeling, statistical inference, and machine learning, especially as applied to fMRI and MRI data. The candidate will have access to multiple large datasets and state-of-the-art computational resources, including HPCs and GPGPUs. Please email a CV, statement of research interests and relevant background, and have three letters of reference sent to Drs. Vinod Menon and Aarthi Padmanabhan at scsnl.stanford+postdoc@gmail.com<mailto:scsnl.stanford@gmail.com>