Multiple Openings for Research Scientists and Engineers in Machine Learning to Reverse-Engineer Intelligence We are looking for exceptionally talented researchers that share our vision: to discover new computational principles of brain intelligence and apply these principles to create fundamentally new algorithms for machine intelligence. We are particularly interested in candidates with expertise in machine learning, computational neuroscience or with strong quantitative background in Mathematics, Statistics, Physics or Computer Science. Our Neuro-Inspired Networks for Artificial Intelligence (ninai.org<https://urldefense.proofpoint.com/v2/url?u=http-3A__ninai.org&d=DwMGaQ&c=ZQs...>) research team is interdisciplinary and international, with expertise ranging from large-scale neurophysiology and brain circuit analysis to deep learning. POSITIONS: We have opportunities in several project components and multiple locations, and all participants will interact extensively across multiple scientific disciplines and multiple sites. Highest-priority topics include: * Developing new architectures for deep networks * Neuro-inspired networks for real-world tasks * Functional modeling of neuronal microcircuits * Probabilistic inference by population codes * Statistical analysis of large-scale neural data from behaving animals THE TEAM: The project is led by Andreas Tolias (PI) and Xaq Pitkow (co-PI), from Baylor College of Medicine, and includes researchers from Caltech, Columbia, Cornell, Rice University, University of Toronto, University of Tübingen, the Allen Institute, and Princeton: Matthias Bethge, Liam Paninski, Ankit Patel, Clay Reid, Sebastian Seung, Thanos Siapas, Raquel Urtasun, Chris Xu, Richard Zemel and Richard Baraniuk. For detailed information about the team and its members, please see our website, ninai.org<https://urldefense.proofpoint.com/v2/url?u=http-3A__ninai.org_&d=DwMGaQ&c=ZQ...>. QUALIFICATIONS: Candidates must have a record of productivity, excellent quantitative skills, good communication skills, and creativity. Experience in Machine Learning and in particular Deep Learning is desired. APPLYING: The positions provide a competitive annual salary and benefits, and outstanding scientific opportunities. Applicants should email a CV, letter of research interests, and contact information for three references to info@ninai.org<mailto:info@ninai.org>. We look forward to hearing from you! Camila Lopez Baylor College of Medicine 713.798.4072 | camilal@bcm.edu<mailto:camilal@bcm.edu>