Research Fellow, Medical Image Analysis [LKCMedicine]

The Lee Kong Chian School of Medicine (LKCMedicine) trains doctors who put patients at the centre of their exemplary care. The School, which offers both undergraduate and graduate programmes, is named after local philanthropist Tan Sri Dato Lee Kong Chian. Established in 2010 by Nanyang Technological University, Singapore, in partnership with Imperial College London, LKCMedicine aims to be a model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised for the quality of its medical expertise, facilities and teaching. The School is transitioning to an NTU medical school ahead of the 2028 successful conclusion of the NTU-Imperial partnership to set up a Joint Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in healthcare, with an expanded scope in the medical humanities. Graduates from the five-year undergraduate medical degree programme will have a strong understanding of the scientific basis of medicine, with an emphasis on technology, data science and the humanities.

We are looking for a Research Fellow to conduct AI for medicine research. The role will focus on developing foundation models to medical image analysis. Foundation models offer a scalable and adaptable solution for medical image analysis by learning generalizable representations from large datasets, enabling effective application across different imaging modalities and tasks. Their ability to perform well with limited labeled data and adapt quickly to new clinical scenarios makes them a powerful tool for advancing AI-driven diagnostics and improving patient care. The position aligns with the School's mission to advance research on AI in medicine and improve patient outcomes through cutting-edge AI technologies.

Key Responsibilities:

• Conduct research on foundation models for medical image analysis, including MRI, CT, X-ray, and endoscopy.

• Ensure all research activities comply with ethical standards and patient data privacy regulations.

• Support research grant preparation, including literature reviews and preliminary data collection.

• Contribute to research outputs, such as manuscript writing and participation in local and international conferences.

• Supervise and mentor undergraduate and PhD students, as well as junior research staff, equipping them with the necessary skills and knowledge to contribute effectively.

• Collaborate with interdisciplinary teams—comprising clinicians, medical researchers, and AI experts—to ensure the developed AI models are accurate, safe, interpretable, clinically applicable, and ethically deployed.

Key Competencies and Qualification Requirements:

• PhD degree in Artificial Intelligence, Computer Science, or a related field from a prestigious institution.

• Good written and oral communication skills.

• Proficiency in developing deep learning models using frameworks such as PyTorch and TensorFlow.

• Research experience in medical image analysis using deep learning algorithms.

• Strong track record in machine learning, computer vision, and medical image analysis, with publications in top-tier AI and medical image analysis conferences and journals, including CVPR, ICCV, ECCV, NeurIPS, MICCAI, TPAMI, TIP, IJCV, TMI, and MIA.

• Familiar with effective strategies for addressing data scarcity, class imbalance, and domain shift in machine learning.

• Interpersonal skill (e.g. Ability to work independently / develop solutions under strict timelines, meticulous and eye for details / excellent organizational / time management skills)

• Entry level candidates are welcome to apply.