Research Assistant / Junior Research Assistant

The School of Architecture is seeking an outstanding candidate to join Prof. Jiaxiu Cai’s research team as Research Assistant / Junior Research Assistant, to support a project that explores the integration of Generative AI and multi-scalar morphological analysis to regenerate Lingnan water-adaptive architectural heritage.

Applicants should have (i) a Master’s degree in a field related to Urban Design, Architecture or Data Science.; (ii) proficiency in GIS (ArcGIS/QGIS) and Adobe Suite (Illustrator, Photoshop).; (iii) experience with Generative AI (Stable Diffusion, LoRA training) or machine learning is highly desirable; (iv) a proven track record of high-quality publications (Q1 journals preferred) and excellent English writing skills; (v) demonstrated independence, critical thinking, and a meticulous approach to research; and (vi) familiarity with the urbanisation and morphological characteristics of the Greater Bay Area.

The appointee will be responsible for (a) conducting multi-scalar morphological analysis of Lingnan water-adaptive heritage, from regional landscapes to architectural elements; (b) developing and manage a specialized image dataset, implementing "Performance-based Captioning" for AI model training; (c) assisting in fine-tuning LoRA models and conducting comparative experiments on AI generative logic; (d) coordinating research activities, including the production of 30 instructional micro-modules and the organization of student workshops; and (e) writing, structuring, and editing of academic publications for international conferences (e.g., ISUF 2026) and high racked journals.

Appointment will initially be made on contract basis for three months, renewable subject to good performance and mutual agreement.

Applicants should submit the following documents in the online application: (1) a CV, (2) a brief cover letter (specifying your research interests and availability), and (3) a portfolio or writing sample. Applications will be reviewed on a rolling basis until the position is filled. Outstanding candidates may be recommended for PhD study in 2026–2027 with opportunities for the Hong Kong PhD Fellowship Scheme (HKPFS).

For more information about Prof. Cai’s research, please visit the project website at For enquiries, please contact Prof. Cai directly at .

The University only accepts and considers applications submitted online for the post above via the CUHK career site. For more information and to apply online, please visit