School of Hotel and Tourism Management
Research Assistant
(Ref. 260903013)
[Appointment period: three months]
Duties
The appointee will assist the project leader in the research project - “Developing an AI-empowered and student-centered institutional self-awareness and well-being support system: From assessment to intervention through parameter-efficient fine-tuning of foundation models”.
The primary role is to take responsibility for frontend development and the integration between the frontend interface and backend AI services to ensure a seamless, robust, and user-friendly system. He/She will be required to:
(a) design, develop, and maintain the frontend interface (web and/or mobile application) to support user assessment, intervention delivery, and interaction with AI modules;
(b) integrate frontend components with backend services (including LLM inference and multimodal processing), to ensure smooth data flow, real-time performance, and consistent user experience;
(c) collaborate closely with AI engineers (for model integration) and psychology researchers to translate functional requirements into effective user interfaces; and
(d) optimise frontend performance, usability, and responsiveness across different devices and platforms.
Qualifications
Applicants should:
(a) have an honours degree in Computer Science, Software Engineering, Information Technology, or a related discipline, or an equivalent qualification;
(b) have proven experience in frontend development, with strong proficiency in modern frontend frameworks (e.g., React, Vue.js) and related technologies (HTML, CSS, JavaScript/TypeScript);
(c) have hands-on experience in integrating frontend applications with backend services and APIs, and be familiar with at least one backend language (e.g., Python, Nodes.js) to facilitate effective collaboration;
(d) have practical experience with version control (Git) and basic deployment workflows (Docker, cloud services such as AWS, Azure, or GCP is a plus);
(e) demonstrate strong problem-solving abilities in debugging frontend and cross-system integration issues, as well as performance optimisation; and
(f) have good communication skills in English and Putonghua, with the ability to translate requirements from both technical and non-technical team members into practical frontend and integration solutions.
Preference will be given to those with previous experience in building user-facing applications for mental health, education, or AI-assisted systems.
Applicants are invited to contact Prof. Maxime X. Wang at telephone number 3400 2160 or via email at maxime.wang@polyu.edu.hk for further information.
Conditions of Service
A highly competitive remuneration package will be offered.
Consideration of applications will commence on 10 September 2026 until the position is filled.
Posting date: 3 September 2026