Post Doctoral Fellowship - Machine Learning & Artificial Intelligence in Neuroscience

University of Saskatchewan; Saskatoon; On-site; CAD 50,000 - 70,000; Full time

Job summary

A leading university is seeking a Post Doctoral Fellow in Neuroscience to develop AI strategies for analyzing OCT images. This role involves collaborative research focusing on early detection algorithms for Alzheimer's and Parkinson's diseases, offering a unique opportunity to advance your career in a dynamic interdisciplinary environment.

Qualifications

• Experience in neuroscience research and familiarity with machine learning/AI.
• Expertise in OCT/OCT-A image analysis preferred.
• Statistical analysis skills are necessary.

Responsibilities

• Develop machine learning strategies for analyzing OCT and OCT-A images.
• Lead aspects of the project and guide junior team members.

Skills

Communication

Statistical Analysis

Algorithm Development

Image Analysis

Education

PhD in Neuroscience, Computational Neuroscience, Machine Learning, or related fields

Job description

Post Doctoral Fellowship - Machine Learning & Artificial Intelligence in Neuroscience

Primary Purpose: The Taghibiglou Research Group (Dr. Changiz Taghibiglou; https://neuroscience.usask.ca/people/faculty/dr.-changiz-taghibiglou.php; https://medicine.usask.ca/profiles/anatomy-physiology-pharmacology/changiz-taghibiglou.php) at the University of Saskatchewan (USask), in collaboration with clinical colleagues, is seeking a talented and motivated Neuroscience postdoctoral fellow. Experience in neuroscience research and familiarity with machine learning/AI/big data processing will be assets. A key responsibility is to develop machine learning strategies for analyzing OCT and OCT-A images from Saskatchewan clinics and international data sources such as UK Biobank, aiming for early detection algorithms for Alzheimer’s and Parkinson’s diseases.

Nature of Work:

This project involves analyzing OCT and OCT-A images from clinics in Saskatchewan and international sources, comparing healthy individuals with those diagnosed with AD and PD, focusing on retinal layer alterations. The goal is to utilize AI to create an early detection algorithm for AD/PD in asymptomatic patients.

Team and Responsibilities:

This is a collaborative, interdisciplinary project. The postdoctoral fellow will report to Dr. Taghibiglou and will lead aspects of the project, including training and guiding junior team members.

Qualifications:

• PhD in Neuroscience, Computational Neuroscience, Machine Learning, or related fields, with expertise in OCT/OCT-A image analysis.
• Experience in neuroscience and algorithm development; brain image analysis experience is preferred but not mandatory.
• Skills in analyzing optical nerve and retinal images, statistical analysis, and algorithm development. Good communication skills are desirable.

Application Process:

Applicants should submit a cover letter, CV, and a relevant publication demonstrating their skills.

Additional Details:

• Department: Anatomy, Physiology, Pharmacology
• Status: 1-year contract, renewable to 2 years pending funding
• Employment Group: Postdoctoral Fellows - PSAC
• FTE: 1.0
• Salary: Commensurate with experience
• Posted Date: 7/18/2025
• Closing Date: Open until filled
• Location: On Campus

The University values diversity and inclusion, prioritizes Indigenous employment, and provides accommodations for applicants with disabilities. The campus is located on Treaty 6 Territory and the Homeland of the Métis, respecting Indigenous communities and fostering indigenization efforts.