Department of Computing
Research Assistant
(Ref. 260703009)
[Appointment period: twelve months]
Duties
The appointee will assist the project leader in the research project – “Collaborative Generative AI”. He/She will be required to:
(a) investigate cutting-edge techniques for foundation large language models and multimodal large language models, with emphasis on pre-training, post-training and model merging/fusion;
(b) develop secure, scalable and efficient infrastructure for data management, distributed training, model evaluation, deployment and ongoing model improvement;
(c) construct and maintain large-scale distributed training systems for large language models, including cluster management, fault-tolerant scheduling, mixed-precision training and end-to-end pipeline optimisation to enable efficient pre-training and fine-tuning at scale;
(d) explore efficient architectural designs for both dense and Mixture-of-Experts (MoE) models, including but not limited to MLA, mHC, Loop Transformer and other parameter-efficient or compute-efficient structures, aimed at enhancing model capacity and training efficiency under constrained computational budgets; and
(e) perform any other duties as assigned by the project leader, the Head of Unit or their delegates.
Qualifications
Applicants should have:
(a) an honors degree or an equivalent qualification, preferably in Computer Science, Artificial Intelligence, Data Science Engineering or a related discipline;
(b) demonstrated expertise in foundation models, generative AI, multimodal learning, machine learning systems, model merging/fusion, or closely related fields;
(c) strong capacity for self-directed learning; and
(d) commitment to open, reproducible and ethically responsible AI research.
Applicants are invited to contact Prof. Hongxia Yang at telephone number 2766 7247 or via email at hongxia.yang@polyu.edu.hk or Mr Jianmin Wu via email at jianmin.wu@polyu.edu.hk for further information.
Conditions of Service
A highly competitive remuneration package will be offered.
The closing date for application is 10 July 2026.
Posting date: 3 July 2026