Fully Funded PhD in Artificial Intelligence for Automated Radiography Report Generation (Chest X-Rays) United Arab Emirates University in United Arab Emirates

A fully funded PhD position is available at United Arab Emirates University for research on "An Integrated Artificial Intelligence Framework for Automated Radiography Report Generation for Chest X-Rays." This project, in collaboration with the University of Toronto (Canada) and NUST (Pakistan), focuses on developing novel explainable large language model algorithms for automated report generation in medical imaging, specifically chest X-rays. The successful candidate will be enrolled full-time in the PhD program and will contribute to advancing AI-driven solutions in healthcare.

Applicants should have a Master’s degree in Computer Science, Computer Engineering, Information Technology, or a related field, with a minimum GPA of 3.0/4.0 from an accredited institution. A mandatory overall IELTS Academic score of 6.5 or equivalent is required. Candidates must demonstrate strong expertise in machine learning, deep learning, and large language models (LLMs), a solid publication record in reputable international venues, excellent communication skills, and proficiency in Python and deep learning libraries such as PyTorch or TensorFlow. All standard PhD admission requirements of UAEU apply, including certified transcripts, recommendation letters, and a CV.

The position is fully funded for four years, including a full scholarship, medical insurance, and a complete tuition fee waiver. The research will be supervised by Amir Ahmad at United Arab Emirates University. The application deadline is March 31, 2026, with the program starting in Fall 2026. Interested candidates should send their CV and motivation letter to [email protected] and review the detailed admission requirements on the UAEU website.

This opportunity is ideal for candidates interested in artificial intelligence, medical imaging, explainable AI, and interdisciplinary research at the intersection of computer science and healthcare. The project offers collaboration with leading international institutions and the chance to contribute to impactful research in automated radiography report generation.