RESEARCH POSITIONS IN SMART IMPLANT AND SPINE AI

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Our group has an opening for Ph.D./master/intern and postdoctoral position applicants. 

 

Projects:

Project 1: Big Data Based Spine Disease Progression Prediction

Our team has established a big dataset with spine MRIs and clinical labels, as well as developed automated novel pipelines for feature detection and segmentation. Our methods include conventional machine learning and deep learning, image processing, etc. These novel approaches can significantly reduce the manual workload of clinical practice as well as provide consistent results. We are looking for a suitable candidate to expand the dataset and established a systematic registry that contains comprehensive medical data, including image (MRI, CT, Xray), clinical information, and follow-up, for multi-domain big data analysis tasks in a spine clinic. Technically, a data structure for the organization, storage, and translation of the dataset needs to be designed. Research involves in human machines interactions resulting in a clinical friendly UI interface with modules of the dataset to upload and download the data flexibly for different tasks, such as image enhancement, auto-diagnosis, image segmentation, pathology prediction with encryption. Our centre is one of the largest spine centres in Hong Kong and routinely screen over 200 patients with spine disorders per week. This presents a guaranteed opportunity for satisfying the patient sample size for this project.

 

Project 2: OI-GPS Orthopaedic Implants General Positioning System

We have developed a device and system for the accurate localization of orthopaedic implants without radiation. The device and system design is a non-contactable medical device with a localization sensitivity smaller than 0.1mm at 1 degree. This novel system and the device will have a significant clinical impact by providing an economical, portable and harmless method for monitoring the true performance (including extension accuracy and fixation stability) of orthopaedics implants. The successful candidate will need to optimize the existing prototype embedded system with improved efficiency and robustness. The candidate also needs to design and perform bench experiments to assess the spatial localization accuracy and precision with high resolution, to be compatible with the commonly used medical equipment regulations. Further studies on animal and patients may be involved.

 

Project 3: Smart Implant and Spine AI

Our team is working on novel diagnosis methods and implants for spine disorders.  The diagnosis tools cover from home-based examinations to hospital screenings.  In comparison with conventional X rays, CTs and MRIs. Our methods are optical light-based, which are cost-effective and non-radioactive. This novel approach is important for patients with spine disorders because they often need repetitive examinations and follow-ups, which can be involved with increased cost and radio exposure.  The projects utilize cutting edge imaging methods combined with artificial intelligence to predict the diagnostic outcomes that a patient may have.  Cross-validation of different optical imaging technologies will be involved, along with automated segmentation and analysis of the original and/or synthesized medical images. Automated 3-D visualization of spinal disorders is a crucial component.

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Supervisor: Dr Teng Grace Zhang is a biomedical engineer with a medical background. Most of Grace’s research combines both disciplines by focusing on the modelling of biological systems with direct clinical applications including telemedicine, auto-diagnosis, surgical planning and tracking to facilitate real-time feedback with minimal radiations. Currently,  Grace is an Assistant Professor, at the Digital Health Laboratory of the Orthopaedics and Traumatology Department, The University of Hong Kong. Previously, Grace worked for nearly seven years as a Scientific Officer at the St George Clinical School of the University of New South Wales (UNSW), Sydney, Australia.

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Supervisor Information Page:

https://www.aimed.hku.hk/teng-zhang

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Qualifications:

For postdoctoral positions, the applicants should have/be

• A Ph.D. degree in Computer Science/Engineering/Math/Physics or a related technical field;

• Experience in one or more of the following areas: 3D Reconstruction, Object detection and Keypoint detection, Linear Algebra, Optimization;

• Fluency in one or more of the following computer language: Python, Matlab, R, C/C++, Java, Javascript;

• Experience working with OpenCV will be a plus;

• Exceptional communication skills, both written and verbal;

• At least have one publication on conference CVPR/ECCV/ICCV/MICCAI/ICML/ICPR/AAAI/IJCAI or journal

       TIP/T-PAMI/TMI/JBHI or other related good conferences or journals.

For Ph.D. positions, the applicants should have/be

• A Bachelor/Master degree in Computer Science/Engineering/Math/Physics or a related technical field;

• Good performance on GPA;

• Familiar with one or more of the following computer language: Python, Matlab, R, C/C++;

• Passionate and active, can cooperate with students, labmates, managers, and other researchers.

• Exceptional communication skills, both written and verbal.

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For Master/Research Assistant positions, the applicants should have/be

• A Bachelor degree in Computer Science/Engineering/Math/Physics or a related technical field;

• Good performance on GPA;

• Familiar with one or more of the following computer language: Python, Matlab, R, C/C++;

• Passionate and active, can cooperate with students, labmates, managers, and other researchers.

• Exceptional communication skills, both written and verbal.

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For Intern positions, the applicants should have/be

• Familiar with one or more of the following computer language: Python, Matlab, R, C/C++;

• Passionate and active, can cooperate with students, labmates, managers, and other researchers.

• Exceptional communication skills, both written and verbal.

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Application:

Please send applications (curriculum vita and contact information of three references) or questions to:

tgzhang@hku.hk.

 

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More Information (funding opportunities/application deadlines):

https://www.findaphd.com/phds/program/biomedical-research-hku-li-ka-shing-faculty-of-medicine/?i586p4119

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Teng Grace Zhang

Assistant Professor

Department of Orthopaedics and Traumatology

The University of Hong Kong

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