Current Opportunities

Join the neuroscience and neurotechnology community at SFU! Current training and research opportunities are posted here as they become available.

INN Community Engagement Manager

The INN’s Community Engagement Manager will play a critical role in the development and implementation of community-engaged research and other community engagement activities. Research projects will include the Brain Resilience Study, a prospective study of British Columbians that aims to understand both the biological and social factors that influence resilience in aging. A complete job description can be found here. To apply, please send your cover letter and resume to on or before February 5, 2024.

postdoctoral Fellowship in Computational Neuroscience

A postdoctoral fellowship in computational neuroscience is available with an immediate start date. The Postdoctoral Fellow will join a cross- disciplinary team of researchers in Randy McIntosh’s lab at the INN. The lab’s research program involves computational modeling and brain imaging to explore changes in cognition across the lifespan and changes resulting from brain damage or disease. A complete job description can be found here. To apply, please send your cover letter and academic CV to

CANSSI Distinguished postdoctoral Fellowship

Dr. Lloyd Elliott is advertising a postdoc position ( in the Department of Statistics and Actuarial Science, at Simon Fraser University (SFU), through a CANSSI (Canadian Statistical Sciences Institute) Distinguished Postdoctoral Fellowship. The position will be supervised by Dr. Lloyd Elliott (SFU) and Dr. Junling Ma (University of Victoria). Details here: and link to apply: (select Project 7: "Fine-scale and functional mapping of brain imaging genetics, and aging").

A wide variety of projects are available (background in every area is not required). Candidates are also encouraged to bring their own projects and collaborations:

  • Brain imaging genetics: voxelwise analysis (including methods for voxelwise genome-wide association studies, and visualization of voxelwise summary statistics), brain imaging before and after COVID-19.
  • COVID-19 host genetics (understanding how human genetic variation modulates COVID-19 severity or susceptibility) and genetic epidemiology: developing polygenic risk scores for COVID-19 or post-acute sequelae of COVID-19, mediation analysis for comorbidities.
  • Statistical epidemiology: projection of case counts for emerging pathogens, estimation of the number of undetected COVID-19 cases. (Related projects in ecology are also available including capture/recapture models and unmarked models).
  • Ecological models for climate change: Determination of how climate change modulates threats from various sources, by genus.
  • Theoretical machine learning, with applications to health research.
  • Homeostasis and aging: develop biomarkers for healthy aging from epigenetics, metabolites, and high-dimensional phenotype data (statistical tools include polygenic risk scores, Bayesian models, and machine learning).