Vacancy: Student Researcher in GIS (Internship)

The deadline to apply for this position has passed. Thanks to all the applicants for their interest. For new vacancies please follow our opportunities page.

Job and project description

The Urban Analytics Lab at the National University of Singapore (NUS) is seeking a student with solid computational and research skills to contribute to a project about generating 3D city models from sparse open data, such as building footprints in absence of lidar point clouds.

The intern will perform one or more of the following tasks preceding the main activities of the project: survey of existing relevant open geo-data around the world, quantitative analysis of OpenStreetMap data, generation of 3D city models from open data, and/or development of a dynamic web GIS portal.

The principal research question of the project Large-scale 3D geospatial data for urban analytics is to investigate whether it is possible to create a 3D city model from (mostly) 2D open data sources such as OpenStreetMap, resulting in a low-cost approach to obtain 3D city models of very large areas suitable for various purposes such as urban analytics. In this position, you will be responsible for the preliminary research of the project, e.g. investigation of currently available open datasets suitable to generate 3D city models, a task which may involve programming.

An earlier related work of the PI is published here (PDF). This project will extend the work, scale it, and implement it on a large number of cities around the world. The project is an excellent opportunity to have an impact in the field of 3D GIS / urban modelling, contribute to the development of methods that range from data acquisition and processing to data quality assurance and visualisation, and derive datasets and methods that could be very valuable to other researchers worldwide – enriching their scientific studies in urban analytics and GIS.

The project has a chance to unlock the potential of 3D geoinformation in areas where there was previously no reliable data available, and contribute to fostering new applications in regions that were previously neglected due to the lack of appropriate datasets.

You will be supervised by the principal investigator of the project Dr Filip Biljecki, NUS School of Design and Environment. This position is closely related to the full-time position advertised concurrently.

Both part-time and full-time work is possible, and only current NUS students are eligible to apply. Both undergrad and grad students are welcome to get in touch, regardless of their school and study programme as long as they are qualified for the job.

Scope and responsibilities

The scope depends on the duration of the internship. The intern will work on some of the following topics:

  • Survey and assessment of the state of the art of open 3D geospatial data.
  • Identification of open datasets around the world suitable to generate 3D city models.
  • Reading and processing geospatial data such as OpenStreetMap.
  • Creating CityJSON datasets.
  • Dissemination and visualisation of data and findings.
  • Documenting the developed code and writing documentation.

Preferred qualifications

  • Experience with programming (preferably Python expertise, but not a must). Having built software used by others and/or scientific software experience is a plus.
  • Excellent communication skills in English.
  • Solid research skills and ability to write in a clear and concise way.
  • Familiarity with geospatial data (and 3D is a further plus), and GIS software/libraries.
  • Capable of identifying and quickly learning the most suitable tools and new programming languages for the project on the go.

Things that may work in your favour during the evaluation of your application:

  • A grasp of data science/machine learning, and expertise with modern tools.
  • A Github account demonstrating prior work, ability to document code, and an open-source stance.
  • Experience with some of the following: Linux, PostgreSQL/PostGIS, R, matplotlib, pandas, and scikit-learn.

You are encouraged to apply even if you do not meet all the requirements above as we offer a stimulating environment supporting you to further develop your skills.

Our offer

  • You will be working on an exciting project at the forefront of 3D city modelling developments, and assisting the team with preliminary work.
  • Possibility to learn more about the topic and make impactful contributions in the field.
  • If coding will be involved, you will have freedom to publish the code as open-source, increasing the visibility of your work and further enhancing your CV.
  • Flexible working environment.
  • The length of the internship depends on the hours involved and can be discussed. Part-time work is possible (e.g. 15 hours a week), while in case of full-time engagement it will be during the vacation period (mid Dec 2019 to mid Jan 2020).
  • The remuneration will be determined according to the university’s range, i.e. the NUS Student Work Scheme (NSWS).

About the Urban Analytics Lab

The NUS Urban Analytics Lab is an interdepartmental multidisciplinary research group established in 2019 focusing on urban analytics, geographic data science, and 3D city modelling at the NUS School of Design and Environment. Its mission is to leverage on spatially enabled data for urban applications, making sense of big geospatial data in the built environment, and catering to disciplines such as architecture, urban planning, and real estate. The group is the first one in Singapore encompassing the entire 3D GIS ecosystem under the same roof: from standardisation and generation of 3D city models all the way to their utilisation and visualisation, while continuously exploring new frontiers in the field.

Application procedure

Please apply by email. Please submit the indication of possessing the qualifications listed above (CV, and optionally additional relevant material such as portfolio and cover letter).

The deadline to apply is 2019-11-25. Please note that only NUS students are eligible to apply. The deadline to apply for this position has passed. Thanks to all the applicants for their interest. For new vacancies please follow our opportunities page.

Appreciate your understanding in advance that only selected shortlisted applicants will be notified.


For more information please contact the principal investigator of the project Dr Filip Biljecki.