AI-Driven Microbiome Profiling for Predicting Ocular Infection Severity

This NILab project offers a unique opportunity for a fully funded PhD studentship in AI-powered bioscience, focused on improving the diagnosis and management of microbial keratitis—a leading cause of blindness. Our project will apply 16S rRNA sequencing and machine learning techniques to predict infection severity, addressing limitations in current diagnostic methods and ultimately improving patient outcomes.

As a PhD student, you will have the chance to work with cutting-edge bioinformatics software tools like KRAKEN2 and programming machine learning models such as neural networks and XGBoost. You will process genomic sequencing data, integrate clinical metadata, and validate your models with external datasets to ensure their clinical relevance and robustness. Your work will contribute to the development of an AI model capable of predicting infection severity based on microbial community profiles.

This project places a strong emphasis on training and development. You will receive hands-on experience with state-of-the-art sequencing platforms, as well as training in bioinformatics, machine learning, and diagnostic protocol development. In addition to these technical skills, you will learn to think critically, solve problems independently, and collaborate within a multidisciplinary research team.

We are seeking a highly motivated student who is eager to learn and contribute to impactful research. This PhD offers a supportive environment for developing the skills necessary to succeed in both academic and industry settings, with ample opportunities for professional growth and collaboration.

Click here to access the application form