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)

• 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.