[Comp-neuro] Postdoctoral positions in computational neuroscience and artificial intelligence

Maxim Bazhenov bazhenov at salk.edu
Fri Mar 2 18:38:06 CET 2018

Applications are invited for post-doctoral research positions in the 
laboratory of Dr. Maxim Bazhenov at the University of California, San 
Diego to study memory and learning and to develop neuroscience inspired 
computer algorithms capable of continual learning and adapting to the 
novel situations and contexts.This project involves close collaboration 
with the experimental laboratory of Dr. Bruce McNaughton (UC Irvine). 
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 neural network models of dynamic interactions between the 
hippocampus and neocortex during learning and memory consolidation in 
sleep and awake based on experimental data. These models will be used to 
derive learning principles that can be combined with advances in 
artificial intelligence and machine learning. An ideal candidate should 
have experience in computational/theoretical neuroscience and a basic 
knowledge of machine learning, or, alternatively, experience in machine 
learning algorithms and some basic knowledge of neuroscience. 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 at ucsd.edu

Maxim Bazhenov, Ph.D.
Professor, Department of Medicine,
Neurosciences Graduate Program,
UCSD, School of Medicine

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