About this role
The intern will research and develop AI and data science solutions, focusing on Generative AI and Machine Learning for healthcare applications. Responsibilities include building data pipelines, optimizing model performance, and collaborating with cross-functional teams to improve operational efficiency.
Candidates must be Year 2 or 3 undergraduates pursuing a degree in Computer Science, Data Science, Business Analytics, or a related field. Proficiency in Python and a strong interest in solving real-world problems using data are required.
What they're looking for
PythonGenerative AIMachine LearningNatural Language ProcessingComputer VisionKnowledge GraphsAgentic AIPredictive Modeling
Frequently asked questions
What does a Uni Internship Jan to July 2027 - Advanced Data Science and AI Innovations Internship at Synapxe do?
The intern will research and develop AI and data science solutions, focusing on Generative AI and Machine Learning for healthcare applications. Responsibilities include building data pipelines, optimizing model performance, and collaborating with cross-functional teams to improve operational efficie…
What skills does this Uni Internship Jan to July 2027 - Advanced Data Science and AI Innovations Internship role need?
Key skills for this role include Python, Generative AI, Machine Learning, Natural Language Processing, Computer Vision, Knowledge Graphs.
How much does a Uni Internship Jan to July 2027 - Advanced Data Science and AI Innovations Internship 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 - Advanced Data Science and AI Innovations Internship 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 - Advanced Data Science and AI Innovations Internship 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.