Uni Internship Jan to July 2027 - Development of use cases in mental health domain

Date: 6 Jul 2026

Location: SG

Company: Synapxe

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 LLM use cases in mental health domain. This ranges from building and supporting proof-of-concept web/mobile applications that tackle problems in mental health domain in Singapore, or collaboration with researchers in mental health research. It will also include literature reviews on mental health and competitive analysis research on industry applications to uncover gaps to fill.

 

The selected intern(s) will assist in following:

 

  • Conduct literature reviews on mental health domain and competitive analysis research on industry applications 
  • Explore agentic AI frameworks, and assess how they can be adapted for mental health-related domain
  • Develop or support proof-of-concept implementations solutions with regards to mental health domain 
  • Perform benchmarking of small open-source models for model application deployment
  • Document system designs, technical setup, experiment results, limitations, and key findings
  • Prepare presentation materials and support knowledge sharing within the team

 

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 in mobile application development, including technologies such as React Native, FastAPI, Supabase, and JavaScript
  • Familiarity with Large Language Models (LLMs), including API-based or open-source models
  • Exposure to agentic AI frameworks is preferred
  • Familiarity with GitHub and collaborative development workflows is an advantage
  • 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 

 

Note: The scope of the project may change depending on organisational priorities, technical feasibility, and project progress. In addition, the students may be asked to support other ongoing AI-related projects and ad hoc duties where relevant.

 

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