Project Description: Glaucoma is the leading cause of irreversible blindness in the world, and early detection is crucial for effective management. This interdisciplinary project aims to develop a novel approach for the early diagnosis of glaucoma by integrating eye-movement analysis and Bayesian statistical modeling. As the successful candidate, you will work closely with a multidisciplinary team of researchers, clinicians, and industry partners to explore innovative methods for identifying early signs of glaucoma through the analysis of eye movements.
Responsibilities: - Conduct literature reviews and stay abreast of recent advancements in oculomotor research, eye-movement analysis and Bayesian statistical modeling.
- Design and implement experiments to collect eye-movement data from healthy individuals and individuals at risk of developing glaucoma.
- Develop and apply Bayesian statistical models for early glaucoma detection using the collected data.
- Collaborate with clinicians to validate findings and translate research outcomes into clinical practice.
- Publish research findings in peer-reviewed journals and present at relevant conferences.