Assistant/Associate Professor in AI for Medical Education

Job Title: Assistant/Associate Professor in AI for Medical Education

University-Level Unit: Duke-NUS Medical School

Faculty/Department-Level Unit: Office of Education

Employee Category: Others

Location_ONB: Outram Campus

Posting Start Date: 13/02/2026

Scope of Position

Duke-NUS Medical School invites applications for a full-time Assistant/Associate Professor in AI for Medical Education within the Office of Education. This innovative role will apply Artificial Intelligence technologies and approaches to support and enhance educational delivery, assessment, and learning experiences, while also contributing to curriculum development that prepares future physicians to practice effectively in an AI-enhanced healthcare environment.

Working in close partnership with MD curriculum leadership, teams, faculty, administrators, and students, the successful applicant will co-lead and support initiatives to develop and integrate AI-powered educational tools across our MD curriculum, conduct research on AI applications in medical education, and design and deliver an AI literacy curriculum. This position represents a unique opportunity to shape the future of medical education at the intersection of technology and healthcare. The successful applicant will be eligible for faculty appointment at the Assistant Professor or Associate Professor level at Duke-NUS; rank will be commensurate with experience, achievement and recognition. The postholder will collaborate with clinician educators and scientists across all health professions and disciplines in the SingHealth Duke-NUS Academic Medical Centre.

Roles and Responsibilities

Roles and Responsibilities:

Partner with curriculum teams to design, implement, and evaluate AI-powered educational tools such as intelligent tutoring systems, adaptive learning platforms, virtual patient simulations, etc

Develop AI applications for personalized learning experiences that respond to individual student needs and learning patterns

Support the development and deployment of AI-driven assessment systems that provide automated feedback, performance analytics, and competency evaluation

Conduct original research on the effectiveness of AI applications in medical education

Publish findings in peer-reviewed journals and present at national and international conferences

Secure internal and external funding to support AI-driven educational innovation projects

Collaborate with Education and IT teams to support learning analytics and educational data management throughout the School

Contribute to the development and delivery of AI literacy curriculum for medical students

Conduct workshops and training sessions for faculty on both using AI tools and teaching about AI

Mentor students, health care educators and investigators interested in Artificial Intelligence for medical education

Participate in the general teaching, service and administrative responsibilities of the Office of Education as determined by their Reporting Officer

Develop strong working relationships with collaborators both within Duke-NUS and the wider SingHealth Duke-NUS Academic Medical Centre

Appropriate duties as assigned by reporting officer

Qualifications

Education:

Doctoral degree in Computer Science, Biomedical Informatics, Data Science, Artificial Intelligence, Machine Learning, Educational Technology, or closely related field

Postdoctoral training or previous faculty appointment in Artificial Intelligence, Medical Education, Educational Technology or other relevant area is desirable but not essential

Technical Expertise:

Demonstrated expertise in Artificial Intelligence and Machine Learning methods and their practical application

Strong programming skills (Python, R, or similar languages) used in AI and data science development

Experience developing, training, and deploying AI/ML models using modern frameworks and tools.

Knowledge of relevant AI domains such as Natural Language Processing, Computer Vision, and/or multimodal learning

Familiarity with learning analytics, data management and educational/healthcare data environments

Understanding of learning management systems or digital learning platforms is advantageous

Experience

Minimum 3 years of experience in the development and practical use of AI/ML applications in educational contexts, healthcare settings or other relevant domains

Experience with learning analytics and educational data mining

Experience with human-centred design and user experience research

Demonstrable commitment to research and scholarship. For example, research productivity, preferably in a higher education institute, healthcare organization or medical education setting; grant funded research as Principal Investigator or lead; peer reviewed research publications; visiting appointments; advisory roles; consultancy; other evidence of scholarly activities; knowledge creation, synthesis, application and dissemination

Competencies:

Knowledge of ethical considerations in AI, including bias, fairness, and privacy

Exceptional time management, organizational skills and the ability to work on multiple projects simultaneously and meet project deadlines

Accessible, calm, flexible, and mature individual with superlative interpersonal skills that permit him/her to work independently as well as in a team environment, to establish credibility with staff at all levels and of different disciplines and backgrounds, and to be persuasive in both one-to-one and group settings

Commitment to maintain confidentiality and exercise discretion in sharing of information.

Excellent written and verbal communication and presentation skills with ability to explain technical concepts to non-technical audiences

Ability to translate Artificial Intelligence / Machine Learning techniques and Data Analytics approaches to medical education and practice

Ability to mentor students and faculty in scholarship within the domain of Artificial Intelligence for medical education

More Information

All applications including a letter of interest and a curriculum vitae should be submitted online.

Informal enquiries are welcome and should be directed to Prof Fernando Bello (f.bello@duke-nus.edu.sg).

We regret that only shortlisted candidates will be notified