The Hong Kong Applied Science and Technology Research Institute (ASTRI) was established by the Hong Kong SAR Government in 2000 with a mission to enhance the city’s global competitiveness. To remain globally prominent, Hong Kong strives to find new ways for its traditional sectors to thrive, and...

The Hong Kong Applied Science and Technology Research Institute (ASTRI) was established by the Hong Kong SAR Government in 2000 with a mission to enhance the city’s global competitiveness. To remain globally prominent, Hong Kong strives to find new ways for its traditional sectors to thrive, and for the potential of emerging sectors to be unleashed. Harnessing the power of technology is key to achieving this.

ASTRI lives up to its mission by pursuing applied Research and Development (R&D) that is delivering technological solutions that strengthen institutions, improve businesses, and benefit communities. Its R&D endeavours focus on five key areas of applications:

  • Smart City
  • Financial Technologies
  • Intelligent Manufacturing
  • Health Technologies
  • Application Specific Integrated Circuits

 

To support our constant endeavour to position Hong Kong as a world-class smart city and an international hub of innovation and technology, we are seeking qualified professionals to fill the following position(s):

Consultant, Machine Learning Platforms (9 months)

Job level Senior
Education Bachelor Degree
Location
Shatin
Employment type Part Time
Industry Information Technology
Job function Information Technology > Software Development
Information Technology > Technical Writing / Consulting
Science / Lab / Research > Research & Development (R&D)
Published On 18/06/2021
ref. CTO/ICS/MLP/C434/201209
Scope of Consultancy Services:
  • Regular meetings with the development team to provide suggestions on the algorithm development and evaluation.
  • Survey the latest state-of-the art CNN and RNN based algorithms for facial anti-spoofing making use of multiple modal data inputs, provide suggestions on algorithms with trade-off between accuracy and complexity 
  • Retrain selected models based on published databases 
  • Consultancy on industry direction, product strategy and academic research scope. Help formulate and focus research and development direction on facial anti-spoofing system. Provide innovative ideas for patent application.  

 

Deliverables:

Milestone 1:

  • Problem Discussion and approaches: To leverage existing expertise and know how in CNN and RNN based algorithms for facial anti-spoofing 
  • Further review: Helping ASTRI team to review the latest state‐of‐the-art CNN and RNN based algorithms for facial anti-spoofing making use of multiple modal data inputs, provide suggestions on algorithms with trade-off between accuracy and complexity 

Milestone 2:

  • Open Lecture: One open technical lecture to be given on technical trend for the latest state-of-the-art CNN and RNN based algorithms for facial anti-spoofing.
  • Technical Meetings: To join three meetings with development team, helping to solve the technical problems encountered by the development team, which include retraining selected models, checking algorithms results, finding out the cause of the problem and improvement solutions  

Milestone 3:

  • Open Lecture: One open technical lecture to provide innovation ideas on CNN and RNN anti-spoofing model for patent application 
  • Technical Meetings: To join three meetings with development team, to discuss possible innovation ideas for patent applications which may include patent landscape search and claim definitions  

 

Requirements:

  • Ph.D. degree in EE, Computer Science or relevant disciplines.
  • 15+ years of academic research experience in face recognition, biometric system security, data privacy and medical informatics is highly preferred. Candidate with less experiences may also be considered.
  • Good understanding of facial anti-spoofing algorithm development and optimization is highly preferred.
  • Strong publication in world top conferences/journals in image processing, biometrics, pattern recognition and artificial intelligence is highly preferred.
  • Broad knowledge and connection in the community-keep abreast of the state of art of the latest progress, other industry players approach and academic R&D directions is highly preferred

 

Application:

Interested candidates please send application (quoting Ref. No.) with detailed resume, current and expected salary to Talent Acquisition via 'APPLY NOW'

Only short-listed candidates will be notified. ASTRI reserves the right not to fill the position. ASTRI is an Equal Opportunities Employer. Personal data provided by job applicants will be used exclusively for recruitment only.