PhD – Modeling cognitive decline in early Alzheimer’s

Doctoral Position Available: Modeling cognitive decline in early Alzheimer’s (J0083)

Background: Alzheimer’s disease (AD) pathology may be present in the brain as many as 10-15 years before symptoms occur. As in most diseases, early treatment, before too much brain damage has been done, is likely to be more effective. However, accurately identifying people at risk of dementia due to AD early, before symptoms appear, is extremely difficult, but critical to initiate treatment to mitigate symptoms and potentially slow cognitive decline.  We have CIHR funding to study people with subjective cognitive decline – those that have issues with memory or cognition, but not enough to be captured by standard cognitive tests. We also study and accurately identify people with mild cognitive impairment.  Both groups have significantly increased risk of later dementia, making them very interesting to study for early AD.

Possible research projects: Two doctoral research positions are possible at McGill University in the departments of Biological and Biomedical Engineering (BBME), Computer Science (CS), and in the Integrated graduate Program in Neuroscience (IPN). Leveraging an existing database of magnetic resonance imaging (MRI) and clinical data from more than 50k subjects, potential PhD research projects include, but are not limited to:

  • cognitive trajectory modeling; what causes cognitive decline?
  • analysis of how biological sex influences cognitive decline
  • development of image processing methods to detect brain atrophy; can patterns of brain atrophy be used for differential diagnostics?
  • development of deep learning or image processing methods to segment hippocampal sub-structures; how do these structures related to decline in memory and cognition?
  • development of new tools for high resolution neuroanatomical structure segmentation
  • creation of prognostic models; will a specific patient remain stable or decline over 3 years?
  • development of new image processing tools (machine learning/ deep learning) to identify and quantify vascular brain lesions (microbleeds, ARIA); how do these lesions correlate with cognitive decline?
  • development of new image processing tools to segment cortical regions to estimate cortical thickness
  • development of new tools to simulate clinical trials

The successful candidate will work with a team of clinicians, engineers, and computer scientists in an open-science environment.

Required qualifications: Candidates should have a masters degree in Neuroscience, Psychology, Computer Science, Engineering, or related discipline with an ability to work independently, good communication skills and some experience in brain-behaviour research. Candidates with a background in computational neuroscience and/or neuroimaging are preferred. Some experience with (or a strong desire to learn) statistical modelling in R or MATLAB, Python, bash/shell programming, neuroimaging pipelines (e.g., MINC-toolkit, ANTs, SPM, FSL, FreeSurfer) and use of computing clusters is a plus, but not required. The work is highly interdisciplinary and collaborative.

Please note that non‐Canadian trainees must have valid student visa to study in Canada.

Location of work: The McConnell Brain Imaging Center (BIC) of the Montreal Neurological Institute (MNI, the Neuro).

Work Schedule: Full time. Starting as soon as possible.

Stipend: $25k funded for 3 years.

How to apply?

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