University of Calgary, Mathematics & Statistics

1188 17334Position ID: 1188-PRCN [#17334]
Position Title: Postdoctoral Researcher in Computational Neuroscience
Position Type: Postdoctoral
Position Location: Calgary, Alberta T2N 1N4, Canada [map]
Subject Area: Computational Neuroscience
Application Deadline: none (posted 2021/02/16)
Position Description:    

*** the list date or deadline for this position has passed. ***

Postdoctoral Researchers in Computational Neuroscience in Alberta, Canada 

We are recruiting talented postdoctoral researchers to participate in a cutting-edge International Network for Brain-Inspired Computation that includes nodes in Montreal, Paris, and the Pacific Northwest of the US and Canada (e.g. University of Washington, Allen Brain Institute). We seek researchers investigating the intersection of mathematics, physics, and neuroscience with interest in the general area of complex network dynamics and emergent activity patterns or representations that drive biological computation. 

The ideal candidates will have a quantitative background (e.g. PhD in mathematics, physics, computer science) along with experience in applying this background to neuroscience. These postdoctoral positions are partially funded by the Pacific Institute for Mathematical Sciences and are aimed to strengthen the link between the Campus Alberta computational neuroscience community at the University of Calgary (Complexity Science Group, Hotchkiss Brain Institute) and the University of Lethbridge (Canadian Center for Behavioural Neuroscience) with the other network members including the Computational Neuroscience Center at the University of Washington. 

Specifically, we are looking for postdoctoral candidates for the following two research themes: 

Theme 1: Investigating how connectivity and dynamics drive network representations. What principles predict how the connectivity structure of neural networks – their connectomes – combine with the dynamics of nodes and edges to control the dynamics and statistics of the network? 
Theme 2: How learning drives network representations. What mathematical principles predict how learning rules, either in artificial or biological networks, select network representations that solve particular computations? 

For both themes, a variety of world-class data sets on the structure and function of the brain are available to guide theoretical advances in the understanding of brain computation, particularly in learning, perception, decision making, and the effects of drugs such as amphetamine and psychedelics. 

The positions are open immediately with primary locations in either Calgary or Lethbridge. The specific start date has to be within five years of being awarded a PhD degree. The positions are for up to two years and they include an annual stipend in the range of CAD$40,000 – $48,000 plus benefits. Opportunities for brief residences in partner nodes (Montreal, Seattle, or Paris) are also available. 

Interested candidates should submit their application package including a cover letter, their CV with a list of publications, brief statement of research interests and their possible start dates in PDF format to Dr. Jörn Davidsen (, Dr. Wilten Nicola ( and Dr. Aaron Gruber ( Applicants should arrange for at least two letters of reference to be sent as well.

Review of applications will begin February 28th, 2021, and continue until the positions are filled. 

For additional information and informal inquiries, please contact Dr. Davidsen, Dr. Nicola or Dr. Gruber. We strive for a diverse and inclusive environment, and encourage applications from members of any identity.

We are not accepting applications for this job through Mathjobs.Org right now. Please see the job description above on how to apply.
Contact: Jörn Davidsen
Postal Mail:
MS 476, 2500 University Dr. NW
Calgary, AB
T2N 1N4
Web Page:

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