School of Sports and Health - Project Officer (AI, CV & Digital Health Integr.)
Republic Polytechnic, Singapore
The Singapore Public Service
Discover a career in the Singapore Public Service that is as rewarding as it is purposeful.[What the role is]
Project Officer – AI, Computer Vision & Digital Health Integration[What you will be working on]
Project: FallSafe+ – AI-Driven Falls Prevention & Recovery Ecosystem
Key Responsibilities:
• Lead the development of the FallSafe+ NeuroCore Machine Learning Model to analyse movement, force, and cognitive data for fall risk prediction.
• Design and implement the GenAI Diagnostic Framework to generate personalised diagnostic reports based on AI outputs.
• Develop front-end interfaces for FallSafe+ NeuroCore, including integration with the IntelliCARE App for result delivery.
• Support the deployment and testing of the FallSafe+ MoveWell Series, ensuring accurate alignment between prescribed interventions and AI risk profiles.
• Assist in the development and implementation of the FallSafe+ MotionLab, including:
o Integration of Computer Vision systems for movement tracking
o Configuration of IoT force sensors and data acquisition pipelines
o Setup of MMSE and ACLS interactive digital kiosk
• Coordinate technical testing and support Principal Investigator in validation trials and usability testing.
Duration of contract: 1 Year (July 2025 – June 2026)
[What we are looking for]
• A Bachelor’s Degree in Computer Science, AI, Data Science, or a related discipline.
• Prior experience or demonstrable skills in machine learning, front-end development, and AI model deployment.
• Familiarity with CV frameworks (e.g., MediaPipe, OpenPose), and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Knowledge of API integration, UI/UX for health apps, and cloud deployment preferred.
• Strong communication and coordination skills.
• Fresh graduates with relevant experience in projects are welcome to apply.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Computer Science Computer Vision Generative AI Machine Learning Model deployment Pipelines PyTorch Scikit-learn TensorFlow Testing UX
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