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Research Fellow / Engineer (Geospatial Data) - MG

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.

The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team to develop a mobile app for visualising geospatial data.

Key Responsibilities

  • Participate in and manage the research project with Principal Investigator (Assoc. Prof. Michael T. Gastner, SIT), Co-PIs (Assist. Prof. Simon Perrault, SUTD; Assoc. Prof. Chen-Chieh Feng, NUS)  and the research team members to ensure all project deliverables are met.
  • Undertake these responsibilities in the project:
  • Implement code for improved cartographic algorithms and thematic map designs.
  • Design human-subject experiments that test how the implemented map designs are used on electronic devices.
  • Perform statistical analysis and report the results in the format of journal articles and conference contributions.
  • Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.

Job Requirements

  • Bachelor’s degree or higher in computer science, statistics, geography, or a closely related field from a regionally or internationally accredited institution.
  • Physical presence in Singapore is required for regular meetings with research team members.
  • Strong research skills as evidenced by publications in internationally recognized journals or conference proceedings.
  • Relevant competence in developing prototypes and creating mobile apps.
  • Experience in working with various types of geospatial data, understanding data structures, and employing appropriate data analysis techniques to extract meaningful insights.
  • Programming experience in at least two of the following languages: C++, R, Python and JavaScript. Knowledge of GIS is desirable.
  • Knowledge of experimental design and computational geometry will be advantageous.

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