Reporting to the Deputy Group Chief Technology Officer, you will propose, develop, and implement advanced Artificial Intelligence / machine learning models and pipelines to augment clinical workflows in NUHS cluster. The candidate will also ensure the adequacy and effectiveness of the models and tools for NUHS.

Key Responsibilities

You will be responsible for the following:

Develop and oversee efficient data collection pipelines across NUHs as well as the institutes we collaborate and work with.
Ensure data governance, security compliance (PDPA/HIPAA/GDPR/etc.), and interoperability for seamless integration.
Work with NUHS IT and clinical teams to automate data extraction and structuring from medical records, imaging systems, and wearable devices
Lead the implementation of AI-driven predictive models for clinical decision support and operational efficiencies.
Establish frameworks for model validation, ensuring AI tools are generalizable, bias-free, and clinically relevant.
Collaborate with data scientists, clinicians, and regulatory bodies to refine AI applications.Design intuitive user interfaces to facilitate AI adoption by clinicians and hospital administrators.
Ensure seamless real-time integration of predictive analytics into Electronic Medical Records (EMRs), dashboards, and reporting tools.
Work with human factors specialists to optimize workflow efficiency and user engagement.Oversee scalable AI deployment across different institutions, ensuring reliability and minimal downtime.
Implement APIs and middleware solutions for seamless interoperability between clusters.
Drive cross-cluster alignment by ensuring standardization in AI outputs, reporting formats, and data-sharing agreements.Engage with executive leadership, healthcare providers, data scientists, and engineers to drive AI-enabled transformation.
Guide junior data scientists in the AIO team, troubleshoot problems so as to achieve end goal
Organising our local AI conferences, showcase NUHS AI capabilities to attract further talents
Develop strategic roadmaps for AI expansion, keeping in mind emerging technologies and regulatory requirements.

Requirements

Master's or Ph.D. in Data Science, Computer Science, Biomedical Engineering, Bioinformatics, or a related field.
Prepare technical documentation, research papers, and presentations for stakeholders.
Strong expertise in Python, R, SQL, and libraries such as TensorFlow, PyTorch, Scikit-learn.
Experience with healthcare data standards (FHIR, HL7, DICOM).
Hands-on experience in deep learning, computer vision, NLP, and time-series analysis.
Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps tools for deploying models.
Strong knowledge of biostatistics, epidemiology, and clinical research methodologies.
Experience in working with large-scale medical datasets and electronic health records.
Understanding of AI ethics, bias mitigation, and interpretability in healthcare AI.
Excellent communication skills to collaborate with clinicians, engineers, and business stakeholders.
Work as a team member to fulfill requirements and tasks assigned by the Reporting Officer

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