University of Hong Kong

Ref.: 534517 Work type: Fractional / Part-time, Full-time Department: Department of Social Work and Social Administration (30300) Categories: Teaching Staff Applications are invited for the position of Senior Lecturer/Lecturer (holding the functional title of Associate Project Director) of JCBeCARE 2.0 -- Compassionate Support Programme for Bereaved Families in the Department of Social Work and Social Administration(Ref.:534517). The appointment rank will be determined based on the qualifications and experience of the successful candidate. The appointee will commence as soon as possible for one year. This leadership position oversees bereavement care for Tai Po Fire victims and may require irregular hours. A fractional or part-time role may be available for outstanding candidates. Qualifications and Requirements Applicants should possess a Master’s degree in Social Work, Psychology, Counselling, Behavioral Health, Public Health, Mental Health, or a related discipline, with at least 5 years’ work experience in clinical practice and teaching or research. Preference will be given to candidates who have a proven track record of excellence in teaching and demonstrated administrative experience. The ideal candidate must possess excellent project management, communication, and interpersonal skills. Duties Manage and coordinate the training programmes of the project; Offer training to professionals on bereavement care and psychosocial topics; Supervise two Research Assistants in conducting evaluative studies; Fulfil any ancillary activities assigned by the Project Director. A highly competitive salary, commensurate with qualifications and experience, will be offered. The appointment carries annual leave, medical benefits, and a University contribution to a retirement benefits scheme. The University only accepts online application for the above post. Applicants should apply online and upload an up-to-date C.V. Applicants are highly encouraged to submit their applications as soon as possible. Review of applications will commence as soon as possible and continue until March 15, 2026 or until the post is filled, whichever is earlier.

Ref.: 534478 Work type: Full-time Department: Department of Orthopaedics and Traumatology, School of Clinical Medicine (21000) Categories: Senior Research Staff & Post-doctoral Fellow, Research Staff Applications are invited for appointment as Post-doctoral Fellow/Senior Research Assistant in the Department of Orthopaedics and Traumatology, School of Clinical Medicine (Ref.: 534478), to commence as soon as possible for one to three year(s), with the possibility of renewal subject to satisfactory performance. Research Context & Project Background The Department of Orthopaedics and Traumatology, School of Clinical Medicine, is seeking a highly motivated and talented researcher to join our multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection, classification, keypoint recognition, image registration, and image synthesis, with the goal of improving diagnostic and therapeutic outcomes. The successful candidate will leverage the unique clinical resources of the Greater Bay Area and the advanced research facilities at the University to develop innovative treatments. Duties and Responsibilities Conduct research on medical image processing algorithms based on computer vision, deep learning and machine learning. Medical imaging modalities cover including but not limited to CT, MRI, X-ray and ultrasound images. Research tasks cover including but not limited to image segmentation, detection, classification, keypoint recognition, image registration, image synthesis, etc. Lead independent research projects and collaborate with partner medical institutions to complete the development, evaluation, translation, integration, deployment and other workflows of medical imaging-related algorithms. Deliver research outputs and achievements, including but not limited to drafting and filing patents, writing and publishing academic papers, and composing research grant proposals. Requirements Applicants with a Master’s degree in Computer Vision, Deep Learning, Computer Science, Image Processing, Biomedical Engineering, or related fields will be considered for the position of Senior Research Assistant. Applicants with a PhD degree in the above-mentioned areas are eligible to apply for the position of Post-doctoral Fellow.  Applicants should possess minimum 3 years of research experience in image processing algorithms, with a solid foundation in computer vision algorithms. Preference will be given to those familiar with the principles of various medical imaging technologies, and possess extensive experience in developing deep learning algorithms Excellent programming skills (e.g., proficiency in Python, PyTorch, OpenCV) and experience in deep learning model optimization and familiarity with AI model deployment are required. Candidates with experience in quantitative CT algorithms, orthopedic imaging algorithms or other related fields are prioritized. Candidates with publications as first author in high-impact journals (medical or AI domains) or top-tier AI conferences are prioritized. Remuneration and Benefits A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.  Application procedure The University only accepts online application for the above post. Applicants should apply online and upload an up-to-date C.V. Review of applications will start as soon as possible and continue until 31 May 2026, or until the post is filled, whichever is earlier. Enquiries about the duties of the post should be sent to Dr. Aaron D.S. Lau (aaronlau@connect.hku.hk).

Ref.: 534447 Work type: Full-time Department: Teaching and Learning Innovation Centre (47500) Categories: Teaching Staff Lecturer in the Teaching and Learning Innovation Centre (TALIC) (Ref.: 534447) The University of Hong Kong is a leading, global university focused on both research and teaching excellence. The Teaching and Learning Innovation Centre (TALIC) is a unit tasked with supporting and enhancing teaching and learning across all disciplines by promoting the best practices in evidence-informed teaching, learning and assessment in Higher Education. Working in TALIC, the appointee will be part of a dynamic and innovative team dedicated to developing and improving teaching and learning. If you are an experienced lecturer who are interested in supporting colleagues across the university and across disciplines, we invite you to apply for the post. Duties and Responsibilities Contribute to CPD programmes for new and experienced members of teaching staff. Provide support and guidance to Research Postgraduate Students involved in teaching. Consult with teachers across different faculties. Requirements Applicants should possess a Master’s degree or above in Education or a related discipline. They should have at least five years of post-qualification teaching experience in higher education and demonstrate excellent interpersonal skills with the ability to communicate effectively within interdisciplinary teams. Possession of a Fellowship of Advance HE would be advantageous. What We Offer The appointment will be made on a two-year fixed-term basis, to commence as soon as possible. A highly competitive salary commensurate with qualifications and experience will be offered, together with contract-end gratuity and University contribution to a retirement benefits scheme at 15% of basic salary. Other benefits include annual leave and medical benefits. How to Apply The University only accepts online applications for the above post. Applicants should apply online and upload an up-to-date CV., along with the contacts of three referees. Review of applications will start from March 2, 2026 and continue until April 17, 2026, or until the post is filled, whichever is earlier.