We seek highly motivated individuals with strong computational backgrounds to work at the interface of machine learning and neuroscience. We have extensive data sets recorded with state-of-the-art optical and electrophysiological methods, spanning normal and abnormal brain function in several experimental preparations. Recent developments in unsupervised machine learning (e.g. deep neural networks) now enable discovery of high-level features of such complex data sets, and provide an opportunity for breakthroughs in understanding brain function.
Conversely, many of the most influential ideas in artificial neural networks have been inspired by biological networks. We therefore also endeavor to implement computational elements revealed by recent experimental findings in order to endow artificial neural networks with more brain-like capabilities.
Candidates should have a strong interest in understanding how the brain works, and expertise in computational science. Prior experience with deep learning algorithms is preferred but not required. Successful candidates will join the highly collaborative and interdisciplinary Brain Dynamics group, which has outstanding research strengths in the areas of learning and memory, decision making, information coding and related diseases such as Alzheimer's, schizophrenia, addiction and stroke. Funding is available through our departmental NSERC CREATE grant in Biological Information Processing, which provides a competitive stipend and unique training opportunities in quantitative sciences and entrepreneurship. Lethbridge is a small city located two hours from Calgary, 90 minutes from the Canadian Rockies, and has a sunny and dry climate.