Job Description
About the Project
This research project, Sensor-Free Machine Learning for Physiological Correction of Brain Functional Imaging: A Lifespan Pilot Study, investigates how machine learning can be used to improve the reliability of functional MRI (fMRI) data without relying on external physiological sensors. The project uses open-access Human Connectome Project lifespan datasets (children, young adults, and older adults) to develop and evaluate models that estimate respiratory and heart-rate variation directly from brain imaging data. The work contributes to advances in neuroimaging methodology and supports the development of accessible, reproducible biomedical data science tools.
About the Role
The Research Assistant will work under the supervision of Dr. Abdoljalil Addeh in the Department of Mathematics and Computing, Faculty of Science and Technology.
This is a flexible, part-time research position, requiring approximately 4–6 ho...
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