PreciX is a pioneering medical technology company dedicated to revolutionising orthopaedic diagnostics through innovative, non-invasive solutions. We collaborate with leading organisations including ASTAR and DXDHub to develop advanced machine learning models that enhance diagnostic accuracy and improve patient outcomes. Current orthopedic diagnostic methods for ACL injuries often rely on subjective assessments and static imaging, leading to delayed diagnosis and suboptimal treatment planning. GATOR addresses these limitations by providing objective, real-time bio-mechanical data during natural movement. The device corrects soft-tissue artefacts through multi-sensory data collection, generating complex knee kinematics time series data that requires sophisticated ML-based analysis to identify altered movement patterns in ACL injured patients, enabling early diagnosis and precise recovery tracking.
The intern will be involved in training and deploying machine learning models to extract meaningful clinical insights from multidimensional kinematics datasets, to transform orthopaedic diagnostics. The intern will also have hands-on experience in co-developing a progressive WebApp for the portal, contribute to backend development, and help test and validate to support integration with our next-generation wearable device.
Tasks and Responsibilities
- Design, train, and evaluate machine learning models to detect biomechanical markers of ACL injury and monitor recovery trajectories
- Preprocess and analyse time-series data collected from multi-sensor wearable devices, ensuring high data fidelity
- Develop, test, and deploy end-to-end ML pipelines, from model training to real-time inference
- Co-develop a Progressive Web App (PWA) for displaying diagnostic outputs and patient insights, optimised for clinician usability
- Contribute to backend API development (e.g. Flask, FastAPI, or Node.js) to support frontend-ML integration
- Work with embedded team to validate model performance and ensure compatibility with device firmware and data protocols
- Assist in documenting ML workflows and software systems for compliance with medical device regulatory requirements
- Collaborate with multidisciplinary teams from ASTAR, DxDHub, and clinical partners to align system outputs with real-world clinical workflows
Requirements
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Biomedical Engineering, or a related STEM field
- Proficiency in Python and key ML libraries (TensorFlow, PyTorch, scikit-learn)
- Experience with data manipulation and visualisation tools (Pandas, NumPy, Matplotlib, Seaborn)
- Solid foundation in machine learning techniques, including supervised learning, deep learning, and time-series modelling
- Familiarity with web development fundamentals, REST APIs, and frontend/backend frameworks (React, Flask, FastAPI preferred)
- Exposure to signal processing or time-series data analysis is a strong plus
- Prior experience with wearable sensor data or biomedical data is advantageous
- Strong analytical and problem-solving skills, with a passion for applying AI in healthcare
- Ability to thrive in a fast-paced, collaborative, and interdisciplinary environment
Kindly note that only shortlisted candidates will be notified.
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- Company:
PreciX Pte Ltd - Designation:
BizOps Manager - Profession:
General Management - Industry:
Healthcare / Fitness / Sports - Location:
Kallang