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Research Assistant I/II

The University of Hong Kong

Apply now Ref.: 529999
Work type: Full-time
Department: Department of Pathology, School of Clinical Medicine (21200)
Categories: Research Staff
Hong Kong

Research Assistant I/II in the Department of Pathology, School of Clinical Medicine (several posts) (Ref.: 529999) (to commence as soon as possible on a one-year temporary basis or two-year fixed-term basis, with the possibility of renewal subject to satisfactory performance).

Applicants should possess a Bachelor or above Degree in Computer Science, Mathematics, Statistics, Intelligent Systems, related disciplines or equivalent. They should be self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in AI deep learning model development in medical images is essential and experiences in histology whole slide imaging analysis on computational pathology is highly desirable.

The appointees will participate in multidisciplinary collaborative research project related to development of multimodality deep learning model for diagnosis and prognosis of sarcomas. He/she will assist in development of deep learning models with state-of-the-art algorithms based on histology whole slide images. He/she may help to implement a software interface for applying multimodality deep learning model in different medical images (X-ray, CT, MRI and whole slide images of histology slides). Enquiries about the duties of the post should be sent to Dr. Maximus Yeung at mcfyeung@hku.hk.

A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits. The appointment on fixed terms will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 10% of basic salary.

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 on October 2, 2024 and continue until December 31, 2024, or until the post is filled, whichever is earlier.

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