The Bazhenov Lab at the University of California, San Diego, is currently seeking to fill a postdoctoral position to study the role of sleep in memory, learning, and forgetting. This exciting project involves close collaboration with experimental labs. The ultimate goal of the work is to advance our understanding of how the human and animal brain learns from experience and how sleep contributes to memory consolidation for recent learning.
The successful candidate will be responsible for designing anatomically realistic biophysical brain network models based on experimental data. These models will be instrumental in uncovering network dynamics involved in memory consolidation, reconsolidation and forgetting during sleep, as well as guiding data analysis and generating innovative experimental predictions. Additionally, depending on the candidate's interests and experience, there may be opportunities to participate in other related lab projects. These projects include developing whole human brain model based on Human Connectome Project (HCP) data and mouse brain model based on the Allen Mouse Brain Connectivity Atlas. Other projects involve applying principles learned from neuroscience to artificial intelligence, focusing on areas such as continuous learning, knowledge generalization, and adaptation to novel situations and contexts. An ideal candidate should have a background in computational/theoretical neuroscience and neural modeling. Programming experience with C/C++ is required, and knowledge of Python and PyTorch is a significant plus. The University of California offers excellent benefits, and the salary will be 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 mbazhe...@ucsd.edu<mailto:mbazhe...@ucsd.edu> Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Institute for Neural Computation, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/
