Postdoctoral Position in Computational Neuroscience/Biophysical Modeling Computational and Applied Mathematics Rice University and Department of Neuroscience Baylor College of Medicine Houston, Texas ----- A postdoctoral position in computational neuroscience is available at Rice University and Baylor College of Medicine, in the laboratories of Steven Cox (Rice University) and Fabrizio Gabbiani (Baylor College of Medicine). Our research focuses on understanding the biophysical mechanisms underlying the implementation of non-linear operations by neurons and neuronal circuits. The postdoctoral research associate will model the cellular and network mechanisms underlying collision avoidance behaviors using advanced mathematical techniques and computer simulations. Modeling will be supported by a large data set of experimental data gathered using electrophysiology, pharmacology, calcium imaging, high-speed video imaging and telemetry. We are looking for a highly motivated candidate with a strong background in computational modeling of single neurons and neuronal circuits. Experience with Matlab and NEURON is required. The position is available for one year, with possibility of renewal for a second year, contingent of performance and funding availability. Salary will be commensurate with level of experience, based on an NIH scale. Applications will be accepted until April 15, 2016. Our labs are located at Rice University and in the adjacent Texas Medical Center, close to many of Houston's cultural and outdoor amenities. For further information about Rice University, the Texas Medical Center and Houston please visit http://www.explore.rice.edu/explore/General_Information.asp or https://www.bcm.edu/about-us/life-in-houston For further informal inquiries and to apply, please send CV, the names and full contact information of two to three references, as well as one to two representative publications to cox@rice.edu and gabbiani@bcm.edu. Equal Opportunity Employer: Females / Minorities / Veterans/ Disabled / Sexual Orientation / Gender Identity.