Research Institute for Federated Learning
Postdoctoral Fellow
(Ref. 260702008)
[Appointment period: twelve months]
Duties
The appointee will assist the project leader in the research project - “AI-based medical image analysis with privacy protection technology”. He/she will be required to:
(a) involve in research and development of advanced artificial intelligence technologies for intelligent medical image analysis, trust worthy clinical decision support, and privacy-preserving multi-centre collaborative learning;
(b) develop AI models for medical image detection, segmentation, registration, localisation, risk assessment, outcome prediction, and treatment-related decision support;
(c) investigate multimodal patient representation learning by integrating imaging, structured clinical data, domain knowledge, and other available patient information;
(d) explore large foundation models, vision-language models, knowledge-enhanced reasoning, and collaborative agent-based frameworks for explainable clinical decision support and multidisciplinary treatment planning;
(e) develop privacy-preserving learning frameworks, including federated learning, distributed intelligent agents, and secure collaborative modelling, to support robust model training and deployment across multiple institutions without sharing raw patient data;
(f) conduct experiments, implement algorithms, analyse results, prepare research publications, and assist in project management, system development, and collaboration with clinical and industrial partners; and
(g) perform any other duties as assigned by the project leader, Director of Unit or their delegates.
Qualifications
Applicants should:
(a) have a doctoral degree or an equivalent qualification and must have no more than five years of post-qualification experience at the time of application;
(b) have solid academic background from a reputable University and research/engineering experience in medical image analysis, computer vision, deep learning, transfer learning, federated learning, privacy-preserving machine learning, large foundation models, vision-language models, knowledge-enhanced AI or collaborative intelligent agents;
(c) have strong programming and implementation skills, preferably with experience in Python, PyTorch/TensorFlow, medical image processing toolkits, model training pipelines, and experimental system development;
(d) have good command of both English and Chinese; and
(e) be self-motivated, responsible and be able to work independently as well as collaboratively in an interdisciplinary research environment.
Preference will be given to those who have publication record in top AI, computer vision, medical image analysis, or biomedical engineering conferences and journals, and to those with experience in clinical AI, Federated Learning, or Foundation Model Adaptation.
Applicants are invited to contact Prof. Di Jiang at telephone number 2766 7281 or via email at di-prof.jiang@polyu.edu.hk for further information.
Conditions of Service
A highly competitive remuneration package will be offered.
Consideration of applications will commence on 9 July 2026 until the position is filled.
Posting date: 2 July 2026