Job Description
7 days ago
Description of project
This research aims to develop a multi criteria decision making model by establishing critical factors that impact adaptive reuse of industrial buildings. Artificial Intelligence (AI) / machine learning and other smart systems will be adapted for digital twin development, multi-factor analysis, predictive modelling, optimization and automation of routine decisions, scenario analysis and design process optimization.
Responsibilities
The appointee is expected to:
Digital Twin Development
Collaborate with the team to develop an urban scale digital twin models.
Integrate IoT, GIS, and other technologies to create comprehensive and interactive urban models.
Test and validate digital twin systems and update models based on real-time data / most recent data feedback.
Documentation & Reporting
Identify data gaps in the information provided by the team.
Maintain comprehensive documentation for all data processes and software applications.
Prepare detailed reports and presentations on findings and digital twin functionalities.
Stakeholder Engagement
• Present findings and project updates to various stakeholders.
Qualifications
Applicants should possess:
Qualifications
Master’s degree in Data Science, Computer Science, Urban Planning, Real Estate & Construction, or a related field.
Strong understanding of Hong Kong industrial buildings, urban development and planning processes.
Experience
2+ years of experience in data analysis or related field.
Demonstrated experience in developing digital twins or simulations in urban contexts.
Proven track record of working with large datasets and complex modelling.
Skills
Proficiency in programming languages such as Python, Java, or C# to develop algorithms and handle data processing.
Experience with databases such as SQL.
Experience in GIS software (e.g., ArcGIS, QGIS).
Familiarity with CAD tools (like AutoCAD, SolidWorks) and simulation software (like MATLAB, Simulink) for creating and testing digital models.
Understanding of IoT platforms (like AWS IoT, Azure IoT) and familiarity with network communication protocols for data integration.
Knowledge of machine learning frameworks for predictive analytics and analysis.
Skills in tools such as Tableau, Power BI, or Matplotlib.
Ability to create clear and effective visual representations of data.
Understanding of cloud services (AWS, Google Cloud, Microsoft Azure) for storage and computational power.
Ability to interpret various statistical results and make data-driven decisions.
Soft Skills
Strong problem-solving capabilities and attention to detail.
Excellent communication and presentation skills.
• Ability to work effectively in a team-oriented environment.
Application procedure
Applicants are invited to send their detailed curriculum vitae and work examples, and direct any enquiries to the Human Resources Office, Hong Kong Chu Hai College [E-mail: recruitment@chuhai.edu.hk], quoting the the reference number.
Application closes on 23 March 2026. Candidature may be obtained by nominations. The College reserves the right to make an appointment by invitation or not to fill this post.
This research aims to develop a multi criteria decision making model by establishing critical factors that impact adaptive reuse of industrial buildings. Artificial Intelligence (AI) / machine learning and other smart systems will be adapted for digital twin development, multi-factor analysis, predictive modelling, optimization and automation of routine decisions, scenario analysis and design process optimization.
Responsibilities
The appointee is expected to:
Digital Twin Development
Collaborate with the team to develop an urban scale digital twin models.
Integrate IoT, GIS, and other technologies to create comprehensive and interactive urban models.
Test and validate digital twin systems and update models based on real-time data / most recent data feedback.
Documentation & Reporting
Identify data gaps in the information provided by the team.
Maintain comprehensive documentation for all data processes and software applications.
Prepare detailed reports and presentations on findings and digital twin functionalities.
Stakeholder Engagement
• Present findings and project updates to various stakeholders.
Qualifications
Applicants should possess:
Qualifications
Master’s degree in Data Science, Computer Science, Urban Planning, Real Estate & Construction, or a related field.
Strong understanding of Hong Kong industrial buildings, urban development and planning processes.
Experience
2+ years of experience in data analysis or related field.
Demonstrated experience in developing digital twins or simulations in urban contexts.
Proven track record of working with large datasets and complex modelling.
Skills
Proficiency in programming languages such as Python, Java, or C# to develop algorithms and handle data processing.
Experience with databases such as SQL.
Experience in GIS software (e.g., ArcGIS, QGIS).
Familiarity with CAD tools (like AutoCAD, SolidWorks) and simulation software (like MATLAB, Simulink) for creating and testing digital models.
Understanding of IoT platforms (like AWS IoT, Azure IoT) and familiarity with network communication protocols for data integration.
Knowledge of machine learning frameworks for predictive analytics and analysis.
Skills in tools such as Tableau, Power BI, or Matplotlib.
Ability to create clear and effective visual representations of data.
Understanding of cloud services (AWS, Google Cloud, Microsoft Azure) for storage and computational power.
Ability to interpret various statistical results and make data-driven decisions.
Soft Skills
Strong problem-solving capabilities and attention to detail.
Excellent communication and presentation skills.
• Ability to work effectively in a team-oriented environment.
Application procedure
Applicants are invited to send their detailed curriculum vitae and work examples, and direct any enquiries to the Human Resources Office, Hong Kong Chu Hai College [E-mail: recruitment@chuhai.edu.hk], quoting the the reference number.
Application closes on 23 March 2026. Candidature may be obtained by nominations. The College reserves the right to make an appointment by invitation or not to fill this post.
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