PDF – Modeling cognitive decline in early Alzheimer’s

Postdoctoral Researcher Position Available: Modeling cognitive decline in early Alzheimer’s (J0081)

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.

Description of tasks: Using an existing database of magnetic resonance imaging (MRI) and clinical data from more than 50k subjects, the postdoctoral fellow will develop novel models of cognitive decline that combine information from (1) sophisticated MRI analysis pipelines to detect patterns of brain atrophy typical of AD, (2) tests of cognition that can be completed quickly in the clinic, and (3) clinically available cardiovascular risk lifestyle factors known to be associated with cognitive decline.  We are also very interested in how sex plays a role in cognitive decline and dementia.  Our goal is to deepen our collective understanding of early AD and develop tools to identify the earliest stages of the disease. In the medium- to long-term, these tools will be used in real-world clinics to accurately identify early-stage AD patients to help clinicians make better treatment decisions, and to make clinical trials more efficient.

The successful candidate will work with a team of clinicians, engineers, and computer scientists in an open-science environment.  The fellowship involves research and publishing papers on projects like statistical cognitive trajectory modeling; group-based analysis; development of differential diagnostic aids; creation of prognostic models; building new tools for high resolution neuroanatomical structure segmentation as well as identification of microbleeds, ARIA lesions and other vascular lesions; development of new tools for clinical trial design and evaluation of all methods in retrospective and prospective datasets.

Required qualifications: Candidates should have a PhD degree (completed no more than 5 years ago) in Neuroscience, Psychology, Computer Science, Engineering, or related discipline with an ability to work independently, good communication skills and experience in brain-behaviour research. Candidates with a strong background in computational neuroscience and/or neuroimaging are preferred. 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 refer to McGill’s requirements on postdoctoral appointments, for conditions and additional information on the status of the position. (In Quebec, a Postdoctoral Fellow is a full‐time student status and trainee category, and the Ministère de l’Education, Enseignement Supérieur et Recherche (MESRS) stipulates that all postdocs must be registered on a university student registration system.)

Please note that non‐Canadian postdoctoral fellows must have valid Citizenship or an Immigration Canada (CIC) work permit to legally work in Canada.

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

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

Salary: Starting at $60k. Unionized, funded position for 2 years.

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