Faculty of Health and Social Sciences
CODE
55005
SUBCODE
55005-MFD-MPD
ENTRY

Sept 2025 Entry

STUDY MODE
Mixed Mode
DURATION

1.5 years (Full-time)
3 years (Part-time)

CREDIT REQUIRED

31

FUND TYPE
Self-Financed
  • This programme is offered within the Postgraduate Scheme in Health Technology.

  • We have a limited quota for admissions. Early applications are strongly encouraged.

Application Deadline
Local - Mixed Mode
Sept 2025 Entry - 30-Apr-2025
Non-local - Mixed Mode
Sept 2025 Entry - 30-Apr-2025

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About Programme
How to Apply
Aims & Characteristics

Programme Aims

This programme is offered within the Postgraduate Scheme in Health Technology, which aims to provide professionals in medical imaging, radiotherapy, medical laboratory science, health technology and others interested in health technology, with an opportunity to develop advanced levels of knowledge and skills in information technology and medical science.

 

A. Advancement in Knowledge and Skills

  • To advance students’ specialisation in their respective professional disciplines to enhance their career paths

  • To broaden students’ exposure to health science and technology, enabling them to cope with the ever-changing demands of work

  • To provide a laboratory environment for testing problems encountered at work

 

Students will develop intellectually, professionally and personally while improving their knowledge and skills in medical data science.  The specific aims of this award are as follows.

  • To introduce students to different aspects of medical data science, including bioinformatics, genetics and genomics, medical imaging etc.

  • To broaden and deepen students’ knowledge and skills in selected areas of medical data science

  • To develop in students an integrative and collaborative team approach to handling complicated medical and clinical data

  • To develop students’ skills in communication, critical analysis and problem solving 
     

 

B. Professional Development

  • To develop students’ ability to perform critical analysis and evaluation in their professional practices

  • To cultivate within healthcare professionals the qualities and attributes that are expected of them

  • To acquire a higher level of awareness and reflection within the profession and the healthcare industry to improve the quality of healthcare services

  • To develop students’ ability to assume a managerial or scientific level of practice 
     

 

C. Evidence-based Practice

  • To equip students with the research skills necessary to perform evidence-based practice in the delivery of healthcare services

 

D. Personal Development

  • To provide channels for practising professionals to continuously develop themselves while at work
  • To allow graduates to develop themselves further after graduation 
     

 

Characteristics

The MScMDS focuses on developing skills for

  1. formulating biological and medical problems into computational problems;

  2. integrating multimodal omics data (e.g., sequence, image and text) from diverse sources; and

  3. developing efficient data analytic systems for medical applications such as modelling aetiology, predicting disease susceptibility and suggesting therapeutic strategies.

     

With the rapid advancements in AI, genomics and biomedical fields, young talents with a solid background in medical data analytics are in high demand.

 

Large quantities of clinical and medical data are now collected in clinical settings and need to be analysed to improve healthcare services. However, the lack of capable personnel is a significant obstacle to healthcare advances using new technologies. MScMDS will fill this immense void in the healthcare sector.

Recognition & Prospects

Some of our subjects will be recognised by the Hong Kong Medical Laboratory Technologists (MLT) Board as continuing professional development (CPD) credits for registered MLTs.

Curriculum

Programme Structure

The Postgraduate Scheme in Health Technology consists of the following awards.

  • MSc in Medical Imaging and Radiation Science (MScMIRS)
  • MSc in Medical Laboratory Science (MScMLS)
  • MSc in Medical Data Science (MScMDS)
  • MSc in Medical Physics (MScMP)

 

The accumulation of 31 credits is required for graduation, including the following.

  • 3 credits of one Compulsory Subject
  • 18 credits from Core Subjects
  • 9 credits from Elective Subjects
  • 1 credit of Academic Integrity and Ethics Subject

 

Compulsory Subject

  • Research Methods & Biostatistics

 

Core Subjects

  • Bioinformatics in Health Sciences
  • Advanced Molecular Biology and Genetics in Medical Science
  • Algorithms in Bioinformatics and Genomics
  • Principles of Data Sciences
  • Data Structures and Database Systems
  • Systems Biology
  • Ethical Issues in Medicine and Research

 

Elective Subjects (Non-HTI subjects 3 credits at most)

  • Dissertation
  • Medical Artificial Intelligence and Data Analytics
  • Latest Advances in Computational Biology
  • Probability and Stochastic Models
  • Machine Learning and Data Analytics
  • Artificial Intelligence & Big Data Computing Programming/Big Data Computing
  • Epidemiology
  • Molecular Technology in the Clinical Laboratory
  • Clinical Applications of Molecular Diagnostics in Healthcare
  • Workshops on Advanced Molecular Diagnostic Technology
  • Genomic Technology and Functional Genomics
  • Advanced Technology and Clinical Application in Computed Tomography/ Advanced Technology and Clinical Application in Magnetic Resonance Imaging
  • Molecular and Functional Imaging: From Body System to Molecules/ Digital Imaging and PACs

 

The four awards within the Scheme share a similar programme structure, and students may take subjects across disciplines.  For subjects offered within the Scheme by another discipline of study, please refer to the information on the MSc in Medical Laboratory Science/MSc in Medical Imaging and Radiation Science/MSc in Medical Physics.

Credit Required for Graduation

31

Programme Leader(s)

Programme Leader   
Prof. Zhang Weixiong   
PhD   
Hong Kong Global STEM Professor

 

Deputy Programme Leader   
Dr Li Hoi Yee, Gloria 
BSc (Bioinformatics), MPhil, PhD

Subject Area
Medical Data Science
Entrance Requirements
  • A Bachelor’s degree in bioinformatics, computer science, computer engineering, electronic engineering, biomedical engineering, physics, applied mathematics, natural sciences, life sciences, biomedical sciences, biology, biochemistry, biotechnology, medical laboratory science, data science, big data analysis, public health or healthcare-related disciplines from PolyU or a recognised institution. Other qualifications may be considered on an individual basis.

 

If you are not a native speaker of English, and your Bachelor's degree or equivalent qualification is awarded by institutions where the medium of instruction is not English, you are expected to fulfil the University’s minimum English language requirement for admission purpose. Please refer to the "Admission Requirements" section for details.

Enquiries

For further programme information, please contact:
The General Office (tel: (852) 3400 8578; email: hti.tpg@polyu.edu.hk)

 

or visit our website at https://www.polyu.edu.hk/hti/study/programmes/taught-postgraduate-programmes_list/ 

Other Information

Suitable candidates may be invited to attend interviews.

Initial Registration Credits

For local students
6 (Full-time)
3 (Part-time)
For non-local students
6 (Full-time)/ (Part-time)

Tuition Fee

HK$7,200 per credit for local and non-local students

Additional Documents Required
Transcript / Certificate

Required

Personal Statement

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