Uni Internship Jan to July 2027 - AI Benchmarking and Automatic Evaluation Framework Development
Synapxe
Singapore, SingaporeInternship19 Aug 2026
About this internship
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 advance the evaluation and benchmarking of Large Language Models (LLMs) for healthcare applications. As AI adoption continues to grow across healthcare, there is an increasing need for robust, standardized, and domain-specific evaluation frameworks to assess model performance, reliability, and safety. This internship focuses on enhancing healthcare AI benchmarking capabilities through the development of evaluation methodologies, benchmarking pipelines, and standardized assessment frameworks.
The Selected Intern(s) Will Assist In Following
Conduct literature reviews on AI benchmarking methodologies, evaluation metrics, and healthcare AI validation frameworks
Understand and extend existing benchmarking pipelines across healthcare use cases such as question answering, clinical summarization, and diagnosis tasks
Refine and experiment with evaluation metrics to improve the assessment of AI model performance
Improve evaluation prompt design and assess its impact on scoring reliability and consistency
Curate and prepare healthcare evaluation datasets to support benchmarking activities
Design and implement standardized benchmarking workflows to improve reproducibility and scalability
Perform experiments comparing different models, prompts, and evaluation approaches
Analyse benchmarking results to identify model strengths, limitations, and potential risks in healthcare contexts
Develop benchmarking dashboards, summary reports, or master benchmarking tables to present findings effectively
Document methodologies, evaluation strategies, and experiment results
Prepare presentation materials and support knowledge-sharing activities 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
Basic understanding of statistics and natural language processing (NLP) concepts, including evaluation metrics
Familiarity with Large Language Models (LLMs) and prompt engineering is preferred
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
Note: The scope of the project may evolve based on organisational priorities. Interns may also be given opportunities to contribute to other ongoing projects and initiatives within the team as required.
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