We are looking for candidates for a PhD position at the Center for Cognitive Neuroimaging, School of Psychology & Neuroscience, University of Glasgow, UK. The post is for interdisciplinary research in between of machine learning, medical imaging, and precision medicine.
* Research title: A novel Deep Learning method for estimating Cortical Thickness trajectories in Alzheimer’s patients and healthy population
* Deadline for student applications: Friday 11th January 2023
* PhD starting date: September 2023
* Duration: 4 years
* Tuition fees covered and stipend of at least £17,668 (UKRI rate 2022/23)
There will be a Project Q&A Session on Friday 25th November, 1030 hrs. (London time)
Alzheimer’s disease (AD) is the most common type of dementia and is a growing public health concern which affects over 50 million people globally, expecting to raise to more than 150 million by 2050. A timely diagnosis and stratification are paramount in determining people who are at risk of progressing from healthy to mild cognitive impairment and Alzheimer’s dementia.
Among available quantitative measurements of disease severity and lifespan progression, mean cortical thickness across the brain has been associated with normal aging and neurodegeneration conditions. Having built trajectories for health population and patients with Alzheimer’s symptoms, the goal of the project is to draft disease progression over time and determine individuals who are at risk. Exploiting recent achievements in deep learning segmentation methods, we will develop a fast and reliable deep learning-based cortical thickness estimator, taking advantage of a unique MRI brain dataset composed by 27,000 structural MRI. The student will build a strong and competitive CV taking advantage from a unique combination of interdisciplinary expertise in deep learning, computational neuroscience, neuroanatomy, and neuropsychological clinical research. The successful candidate is required to have prior knowledge in Machine Learning and/or a degree in related field.
Here the details of the position: