POSITION: We seek several highly motivated postdoctoral research fellows for a collaborative team project building statistical tools for interpreting large scale neural recordings. The fellows will develop new methods and applications of probabilistic graphical models to infer statistical interactions amongst neurons and with their environment. The tools will be validated in neural network simulations, tested in physiological recordings, and made widely available to the neuroscience community for understanding data from next-generation experiments. TEAM: Fellows will join principal investigators and theorists Krešimir Josić, Genevera Allen, Xaq Pitkow, Ankit Patel, and Robert Rosenbaum. The team will interact closely with experimentalists including co-Investigator Andreas Tolias and several other labs interested in applying novel methods we develop. Fellows will also be members of the new Center for Neuroscience and Artificial Intelligence housed at the Baylor College of Medicine and supported in part by the NSF NeuroNex program. The Center brings together interdisciplinary researchers from across Houston, including members from Baylor College of Medicine, Rice University, University of Houston, and University of Texas Health Sciences. Researchers at the Center contribute diverse expertise in fields including neuroscience, machine learning, statistics, physics, computer science, electrical engineering, and applied mathematics. QUALIFICATIONS: Candidates must have outstanding mathematical skills, a PhD in a relevant quantitative discipline, and expertise in probabilistic graphical models or statistical machine learning. APPLYING: Applicants should email a letter of research interests and CV to Camila Lopez (Camila.Lopez@bcm.edu), along with contact information for three references. We look forward to hearing from you!