Uni Internship Jan to July 2027 - Development of Risk Detection and Prediction via Sequential Data

Synapxe; Singapore; On-site; SGD 10,044 - 15,624; Part time

Job summary

Synapxe is offering an internship to join the Data Science & AI team in Singapore. You will work on healthcare AI/ML solutions, focusing on ECG, heartbeat, and time-series data to build predictive models and deploy them to edge devices.

The role emphasizes practical experience, learning new tools, and contributing to impactful health tech projects that enhance patient outcomes.

Qualifications

• Pursuing a relevant Bachelor's degree; Year 2 or 3.
• Strong Python programming with solid coding fundamentals.
• Experience with AI/ML and deep learning libraries.
• Hands-on experience in time-series data analysis and deep learning modelling.
• Willingness to learn new tools and adapt to evolving environments.
• Excellent communication and problem-solving skills.

Responsibilities

• Conduct exploratory data analysis on heartbeat, ECG, and PPG datasets.
• Design methodologies for analysing and predicting AF and other conditions.
• Experiment with hyperparameters and model exploration.
• Perform post-model training analysis using explainable AI techniques.

Skills

Python programming

Time-series analysis

Deep learning basics

Communication skills

Team collaboration

Education

Undergraduate Year 2/3 in a relevant field

Tools

PyTorch

TensorFlow

Scikit-learn

Job description

Join Synapxe as an intern and see how you can contribute in powering a healthier Singapore. Internship@Synapxe is where curiosity meets impact! You would be able to gain practical experience, hone your skills, and be part of meaningful work that improves health through technology!

As an intern you will join the Data Science & AI team to explore advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques for healthcare applications. Sequential data such as ECG signals, heartbeats, speech, and gene sequences contain rich information that can support risk detection and prediction. This internship offers the opportunity to work with real-world healthcare datasets and develop predictive models using state-of-the-art AI/ML approaches.

The Selected Intern(s) Will Assist In Following

• Conduct exploratory data analysis on heartbeat, ECG, and PPG datasets.
• Design methodologies for analysing and predicting Atrial Fibrillation and/or other healthcare conditions that may require invasive measurements.
• Conduct model experimentation through hyperparameter tuning and model exploration.
• Perform post-model training analysis using explainable AI techniques.
• Explore and implement model quantisation techniques to improve efficiency and deployment readiness.
• Support the deployment and testing of models on mobile or edge devices.

About You

• Undergraduate currently in Year 2 or Year 3, pursuing a degree in Business Analytics, Business Artificial Intelligence Systems, Information Systems, Computer Science, Computer Engineering, Data Science, or a related discipline
• Strong proficiency in Python programming, with solid coding fundamentals
• Experience with AI/ML and deep learning libraries (e.g. PyTorch, TensorFlow)
• Hands‑on experience in time‑series data analysis and deep learning modelling
• Good understanding of AI/ML concepts, including model development and evaluation
• Adaptability in dynamic and evolving environments, with willingness to learn new tools and techniques
• Self‑driven and proactive mindset, with the ability to learn independently
• Independent, fast‑learner, and self‑driven
• Good team player with strong analytical and communication skills
• Ability to multitask and work effectively as part of a multidisciplinary team
• Passionate and keen to make a difference to re‑imagine the future of HealthTech

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