NATIONAL UNIVERSITY OF SINGAPORE

Research Assistant, Architecture

Job Description

We are looking for a Research Assistant to work on a project entitled “Data modelling and integration for environmental-behavioural data analytics”. The aim of the project is to explore the integration of building models, geospatial data and time-based sensor data within a common CityGML data model, in order to support environmental-behavioural data analytics research. The objectives of the research proposal are threefold:

  1. Develop a common data model as an extension of CityGML that supports the integration of the various kinds of data resources — to support environmental- behavioural data analytics —, thereby resolving ontological differences between these data resources.
  2. Develop the necessary algorithms and procedures to automatically convert and integrate the various data resources into the common CityGML-based data model.
  3. Demonstrate and test the common data model and data integration algorithms in support of environmental-behavioural data analytics.

This research builds upon previous research (https://ifc2citygml.github.io) in the conversion of Building Information Models in the Industry Foundation Classes (IFC) format into CityGML and extends on its results.

Qualifications

The candidate is expected to have expertise in computer programming or scripting. Additional expertise in data analytics or Geographic Information Systems (GIS) is desirable. Alternatively, an understanding of data formats and standards, and practical knowledge of Building Information Modelling (BIM) is beneficial as well. The candidate will work within a team. The candidate will have a Bachelors, Masters or PhD degree in architecture, geography, computer science, or closely related field from a reputable university.

Job responsibilities may include:

  1. Literature review and data collection
  2. Requirement specification and general data modelling
  3. Conversion rule development in Java
  4. Data conversion, integration and testing
  5. Data analytics
  6. Documenting the research done

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