Master Thesis project: Multi-Modal Data Analysis on Retina Data Using AI

Project Overview:

Age-related Macular Degeneration (AMD) is a progressive eye condition that affects the macula, the central part of the retina responsible for sharp, central vision. It is one of the leading causes of vision loss in individuals over the age of 50. This project explores the application of artificial intelligence (AI) for multi-modal data analysis in the context of retinal data. By integrating diverse data types, such as in vivo imaging and omics data, the aim is to enhance the precision of retinal disease diagnosis, monitor disease progression, and develop personalized treatment strategies for conditions such as Age-related Macular Degeneration (AMD) and Diabetic Retinopathy.

Research Objectives:

1. Develop AI algorithms to integrate multi-modal data, including optical coherence tomography (OCT), optical coherence tomography angiography (OCTA), electroretinogram, microelectrode arrays, and various omics data (genomics, proteomics, metabolomics).
2. Create AI models capable of accurately identifying and classifying retinal diseases by analysing the combined imaging and omics data.

Eligibility:

• Master students with a major in computer science, bioinformatics, biomedical engineering, artificial intelligence, or a related area in the final stage of master level studies are invited to apply.
• Proficiency in programming with Python or MATLAB.
• Experience or interest in machine learning, medical data analysis.

If you interested, send your CV to Zohreh Hosseinzadeh(zohreh.hosseinzadeh@radboudumc.nl) and Nadieh Khalili(nadieh.khalili@radboudumc.nl), or contact Tom Claassen (tom.claassen@ru.nl) for more information.