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NTU Main Campus, Singapore, Singapore
Onsite
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.
The MVAIT Lab at LKCMed seeks to hire a Research Associate (RA) who will play a role in pioneering research on medical image processing, medical visual technology and LLM, and the interface of AI algorithms with surgical robotics. The RA will design and implement cutting-edge algorithms and also be actively involved in the development AI tools tailored for different medical domains. These are efforts to bridge the gap between advanced computational framework and practical medical use cases. The tools and framework developed by the RA will be meticulously adapted to meet the needs of clinicians, radiologists, and biologists, assisting them in their daily tasks and pioneering research. Ultimately, this position plays a pivotal role in LKCMed's overarching mission to leverage technology to enhance healthcare outcomes and propel the institution to the forefront of medical advancements.
Key Responsibilities:
Design and implement AI algorithm models to analyze multimodal medical datasets (including MRI, CT, X-ray, OCT, and ultrasound images) for high-precision medical organ segmentation, 3D modeling research, and intelligent diagnosis.
Explore and develop the application of large-scale pre-trained models in medical scenarios, including but not limited to intelligent consultation systems based on large language models and disease management systems utilizing multi-modal large model technologies.
Develop, test, and optimize AI software systems for various medical tasks, ensuring their applicability and accuracy in real-world medical environments.
Utilize data storage technologies to manage multimodal medical data securely and efficiently, ensuring data privacy while providing high storage capacity to accelerate AI model training and inference.
Enhance the visualization capabilities of AI software system outputs using VR/AR equipment and 3D visualization technologies, aiding clinical observations and assisting interns in training and rapid learning.
Collaborate with the team to systematically complete research and development tasks, assisting in the development of AI-assisted robotic solutions for surgical procedures, including pre-operative planning and intra-operative guidance.
Ensure that all research activities adhere to ethical guidelines and patient data privacy regulations.
Stay updated on the latest advancements in medical imaging, image processing, robotics, and large language models, ensuring that the research remains at the forefront of the field.
Collaborate with external researchers and interdisciplinary teams (including medical professionals, AI experts, and research professors) to ensure the necessity, professionalism, rationality, and practicality of the research.
Write research proposals, grant applications, and contribute to the team's strategic research direction.
Mentor and train junior researchers, students, and interns, ensuring they possess the necessary skills and knowledge to contribute effectively to the research.
Competencies and Qualification Requirements:
Master degree in Computer Engineering, Computer Science, or a related field from a prestigious institution.
Extensive experience in deep learning, AI, computer vision, 3D reconstruction algorithms, and large-scale Pre-trained Models.
A solid research foundation and engineering experience in the AI medical field, proficient in programming languages and frameworks such as Python, C++, Pytorch, Tensorflow, Opencv, and COLMAP.
Experience in software system engineering, capable of designing a well-structured system architecture to support the implementation of AI medical software.
Proficiency in SQL and other data storage technologies, able to apply them flexibly and effectively in the AI medical field, ensuring data storage performance and security.
Experience analyzing and interpreting medical imaging datasets, particularly ophthalmic imaging data, with an understanding of the nuances and peculiarities of such datasets.
A deep understanding of ethical considerations, patient data privacy regulations, and other compliance-related aspects of medical research.
Ability to collaborate with interdisciplinary teams, including medical professionals, AI experts, and research professors.
Proactive and self-driven, capable of developing and managing multiple tasks and projects simultaneously.
Excellent written and verbal communication skills in English; proficiency in additional languages is a plus.