Research Assistant/Associate, AI in Medicine
Centre of AI in Medicine is a university-level research centre with the mission to bridge the gap between cutting-edge Artificial Intelligence (AI) technologies and practical applications in healthcare, The key objective is to spearheadresearch and development to revolutionise patient care and inform public health policies.
For more details, please view https://www.ntu.edu.sg/c-aim
We are seeking a Research Assistant / Research Associate to contribute towards the daily operational needs and strategic research priorities of the NTU Centre of AI in Medicine (C-AIM). The role will support the smooth running of C-AIM’s infrastructure, AVIT systems, administrative processes, procurement, audits, documentation, and coordination activities, ensuring that the Centre’s day-to-day functions are reliable, efficient, and responsive to project and stakeholder needs.
In parallel, the candidate will provide data science and AI/ML modelling support for strategic healthcare AI projects, including clinical and biomedical data preparation, feature engineering, statistical modelling, machine learning model development, validation, performance evaluation, workflow prototyping, reproducible analysis, technical documentation, grant and proposal support, and coordination with internal and external collaborators. Through this dual operational and research-facing role, the candidate will help C-AIM translate AI innovations into practical healthcare applications that advance patient care, health system improvement, and responsible AI implementation in medicine.
Primary Responsibilities:
Daily Operations, Infrastructure and AVIT Support
Manage, operate and maintain C-AIM’s AVIT, computing and infrastructure resources, including microaccess laboratories and AI simulation rooms, to ensure readiness for meetings, events, demonstrations, teaching, research activities and stakeholder engagements;
Provide day-to-day technical support, troubleshooting and liaison with institutional teams, vendors and service providers for equipment setup, servicing, procurement and upgrades;
Maintain inventories, usage records, documentation and operational trackers to support efficient centre operations, audit readiness and continuity of services.
Data Science, AI/ML Modelling and Technical Research Support
Support healthcare AI projects involving statistical modelling, machine learning, predictive analytics, natural language processing, multimodal data integration or other AI/ML approaches relevant to clinical, biomedical or health system applications;
Assist with data extraction, cleaning, harmonisation, feature engineering, exploratory analysis, model training, validation, benchmarking, calibration and performance evaluation using appropriate statistical and machine learning methods;
Develop, test and document reproducible analytical workflows, scripts, notebooks, pipelines, dashboards or prototypes to support AI/ML model development and evaluation in healthcare settings;
Prepare technical summaries, model outputs, visualisations and interpretation notes to support research meetings, grant applications, project reports, manuscripts and stakeholder-facing communications.
Healthcare AI Implementation and Project Support
Support strategic healthcare AI implementation projects by assisting with needs assessment, workflow mapping, stakeholder documentation, user feedback collection and translation of research findings into practical implementation recommendations;
Assist with data preparation, processing, statistical analysis, model development, validation, evaluation and documentation for AI-enabled healthcare projects, ensuring that technical outputs are robust, interpretable and aligned with clinical or implementation needs;
Contribute to the development, testing and evaluation of AI/ML workflows, prototypes, dashboards or tools that support responsible deployment, monitoring or evaluation of AI applications in healthcare settings;
Support deployment, testing and maintenance of AI/ML applications on suitable institutional or cloud-based platforms, in coordination with relevant technical, governance and stakeholder teams.
Research Coordination, Documentation and Communication
Prepare and maintain research protocols, study materials, implementation notes, project reports, presentation materials and progress updates for C-AIM projects;
Coordinate communication across data science teams, clinical or institutional collaborators, technical partners, vendors and administrative units to support timely project delivery and clear stakeholder engagement;
Support the preparation of grant applications, research proposals, conference materials, posters, manuscripts, ethics submissions and other outputs arising from healthcare AI, data science and AI/ML modelling work.
Research Administration, Compliance and Centre Support
Handle procurement, purchase requests, vendor coordination, asset tracking and resource planning for both routine centre operations and research project needs;
Support audits, compliance checks, institutional reporting and documentation processes to ensure alignment with NTU, C-AIM and project governance requirements;
Assist with research and legal agreements, project records, ethics or governance submissions where applicable, and coordination of administrative workflows required for collaborative healthcare AI projects;
Coordinate with finance, procurement, human resources, estates, IT and other administrative departments to resolve operational matters and support smooth centre functioning.
Required Competencies and Qualifications:
Bachelor’s (for Research Assistant) or Master’s (for Research Associate) degree in Data Science, Statistics, Computer Science, Engineering, Biomedical Engineering, Health Informatics, Bioinformatics, Computational Biology, Applied Mathematics, Artificial Intelligence, Machine Learning, or a closely related quantitative discipline relevant to healthcare AI and AI/ML modelling.
Training or experience in data science, statistical analysis, machine learning, predictive modelling, natural language processing, deep learning, biomedical data analysis, clinical data analytics or related AI/ML methods.
Ability to support healthcare AI studies involving data preparation, feature engineering, model development, validation, benchmarking, calibration, performance evaluation, interpretability analysis and translation of technical outputs into actionable research insights.
Competence in preparing, cleaning, organising and analysing structured or unstructured datasets, including clinical, biomedical, imaging, omics, text, survey, workflow, interaction-log or implementation outcome data where applicable.
Proficiency or strong working familiarity with programming and data analysis tools such as Python, R, SQL, Git, Jupyter notebooks, machine learning libraries, statistical packages, visualisation tools or equivalent platforms is expected.
Experience with reproducible analytical workflows, model documentation, experiment tracking, version control, data governance, privacy-aware analysis or deployment-oriented AI/ML workflows is advantageous.
Strong written and verbal communication skills, with the ability to prepare technical documentation, research protocols, analytical reports, grant or proposal inputs, presentations, ethics documents and stakeholder-facing updates clearly and accurately.
Good interpersonal and coordination skills, with the ability to liaise professionally with research teams, clinical or institutional collaborators, technical partners, vendors and administrative units across multidisciplinary healthcare AI projects.
Practical ability or willingness to support daily centre operations, including AVIT setup, equipment readiness, infrastructure coordination, inventory tracking, procurement documentation, audit preparation and liaison with vendors or institutional service teams.
Strong organisational skills, attention to detail and interest in healthcare, AI in medicine, responsible AI implementation, digital health, clinical data science, biomedical AI, machine learning or health system improvement.