Applications are invited for post-doctoral research position in the laboratory of Dr. Maxim Bazhenov at the University of California, San Diego to study memory and learning and to develop neuroscience inspired algorithms capable of continual learning, generalization of knowledge and adaptation to the novel situations and contexts.This project involves close collaboration with the experimental laboratory of Dr. Bruce McNaughton. The ultimate goal of the work is to advance the knowledge of how human and animal brains learn from experience and apply these principles to the artificial systems to enable continuous learning without catastrophic forgetting. The successful candidate will collaborate with a team of researchers to design anatomically realistic neuronal network models of dynamic interactions between the hippocampus and neocortex during learning and memory consolidation in sleep and awake based on experimental data. An ideal candidate should have experience in computational/theoretical neuroscience and a basic knowledge of machine learning. Experience with hierarchical learning, reinforcement learning, and/or goal-directed decision-making would be particularly helpful. The University of California offers excellent benefits. Salary is based on research experience. Applicants should send a brief statement of research interests, a CV and the names of three references to Maxim Bazhenov at mbazhenov@ucsd.edu -- Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Neurosciences Graduate Program, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/