About this role
The intern will conduct exploratory data analysis on healthcare datasets and design methodologies to predict conditions like Atrial Fibrillation. Responsibilities include model experimentation, applying explainable AI, and supporting deployment on mobile or edge devices.
Candidates should be Year 2 or 3 undergraduates in Computer Science, Data Science, or related fields with strong Python proficiency. Experience with deep learning libraries and time-series data analysis is required.
What they're looking for
PythonPyTorchTensorFlowTime-series Data AnalysisDeep LearningExploratory Data AnalysisExplainable AIModel Quantisation
Frequently asked questions
What does a Uni Internship Jan to July 2027 - Development of Risk Detection and Prediction via Sequential Data at Synapxe do?
The intern will conduct exploratory data analysis on healthcare datasets and design methodologies to predict conditions like Atrial Fibrillation. Responsibilities include model experimentation, applying explainable AI, and supporting deployment on mobile or edge devices. Candidates should be Year 2 …
What skills does this Uni Internship Jan to July 2027 - Development of Risk Detection and Prediction via Sequential Data role need?
Key skills for this role include Python, PyTorch, TensorFlow, Time-series Data Analysis, Deep Learning, Exploratory Data Analysis.
How much does a Uni Internship Jan to July 2027 - Development of Risk Detection and Prediction via Sequential Data at Synapxe pay?
The employer did not list a salary for this role. Most similar Singapore roles publish their band on the job page.
Is this Uni Internship Jan to July 2027 - Development of Risk Detection and Prediction via Sequential Data role remote, hybrid, or on-site?
This role is on-site, based in Singapore.
How do I apply for this Uni Internship Jan to July 2027 - Development of Risk Detection and Prediction via Sequential Data role?
You can apply directly on Synapxe's careers page. ApplyLah can tailor your résumé and cover letter to this exact role in seconds first.