Post-doctoral Fellow in the Division of Spine Surgery

Pok Fu Lam, Hong Kong
19 Jun 2019
End of advertisement period
10 Jul 2019
Contract Type
Fixed Term
Full Time

Work type: Full-time
Department: Department of Orthopaedics and Traumatology (21000)
Categories: Academic-related Staff

Applications are invited for appointment as Post-doctoral Fellow in the Division of Spine Surgery of the Department of Orthopaedics and Traumatology (Ref.: 496901), to commence as soon as possible for one to three years, with the possibility of renewal subject to satisfactory performance.

Applicants should have a Ph.D. degree in computer science, applied mathematics, artificial intelligence, physics, neuroscience, or a related discipline. They should have technical knowledge of common machine learning algorithms, especially deep learning; familiarity of algorithms such as pattern recognition, probability statistics, and optimization; competence in at least one of the common machine learning or deep learning frameworks such as Caffe, Tensorflow, PyTorch, Matconvnet, Torch, MXNet, XGBoost, and Spark; and solid programming skills using C/C++, Java, Python, Matlab, R, Julia, etc. They should also have initiative, strong problem-solving skills, excellent logical thinking, data sensitivity, and the ability to work independently as well as in a close multi-disciplinary team. The ability to read and write English journal articles is essential.

The appointee will participate in the research projects on systematic/standardized acquisition of medical images, feature extraction, automatic diagnosis, 3D visualisation, and disease development prediction.  Shortlisted candidates will be invited to an interview. Enquiries about the duties of the post should be sent to Dr. Jason Cheung at  Those who have responded to the previous advertisement (Ref.: 495470) need not re-apply.

A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.

The University only accepts online applications for the above post.  Applicants should apply online and upload an up-to-date C.V., and provide at least one referee's name and contact details. Review of applications will start as soon as possible and continue until July 10, 2019, or until the post is filled, whichever is earlier.

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