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Open nowPosted today

Research Assistant (GeoAI / GIS / Urban Flood Resilience)

MyCareersFuture93,320 open roles

Pay
SGD 4,000 – SGD 7,000 a month
Where
West, Singapore
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Your applicationOpen nowResearch Assistant (GeoAI / GIS / Urban Flood Resilience)MyCareersFuture · West, Singapore

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  5. 34.0%30 days
This job: posted today

MyCareersFuture median: 7 days open

The posting

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link - https://careers.nus.edu.sg/job/Research-Assistant-%28GeoAI-GIS-Urban-Flood-Resilience%29/34646-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are seeking a motivated Research Assistant to join the project “Assessing Urban Flood Resilience against Climate Extreme with GeoAI in Southeast Asia.” The project will develop a GeoAI-based framework for urban flood resilience using multimodal geospatial data, including GIS, remote sensing, street-view imagery, and socio-demographic data in Southeast Asia.

Key Responsibilities

  • Process, integrate, and analyse multimodal geospatial data.
  • Develop and evaluate GeoAI / machine-learning methods for urban flood risk and resilience mapping.
  • Conduct spatial analysis, statistical analysis, and visualisation using Python, R, and GIS. Support comparative analyses across Southeast Asian cities.
  • Conducting standard research activities, such as literature reviews and contributing to research publications and reports.
  • Work closely with the PI, Co-PI, and student researchers, and assisting the team in various activities such as project management, administration, and funding applications.

Qualifications

  • Bachelor’s or Master’s degree in Geography, GIScience, Geomatics, Remote Sensing, Computer Science, Data Science, Urban Planning, or a related field from a reputable university.
  • Strong GIS and spatial analysis skills, with programming experience in Python and/or R.
  • Experience with geospatial data processing and visualization.
  • Preferably knowledge of GeoAI, machine learning, deep learning, or computer vision is preferred.
  • Experience in urban climate, flooding, disaster risk, remote sensing, or urban analytics is an advantage.
  • Strong analytical, communication, and academic writing skills.
  • This is an entry-level position, but applicants with some research experience, publications, and evidence such as a developed repository will be prioritized.

Note: Candidates do not need expertise in all areas. Applicants with a strong geospatial foundation and programming skills are encouraged to apply.

Application

Our offer

  • You will be working on a compelling project at the forefront of geographic information modelling, climate resilience, and disaster management.
  • Work in a research and educational environment where you may not only contribute to your own personal development, but also to others, especially through collaborations.
  • Opportunity to make impactful contributions in the field, on a globally relevant topic, and opportunity to build a research portfolio.
  • Visibility and exposure of your work.
  • Flexible working environment.
  • Exploring new technologies and opportunity to experiment with the state of the art.
  • The remuneration will be determined according to the university’s salary range depending on the degree and experience.

Duration and start

The appointment is for one year. The expected start of the job is in January 2027.

Location

The main campus of the National University of Singapore. This is not a remote position.

How to Apply

Please submit the indication of possessing the qualifications listed above (CV, and optionally additional relevant material such as portfolio and cover letter), and do so preferably in PDF format.

We appreciate your understanding that only applicants shortlisted for the interview will be notified. Shortlisted candidates will later be asked to provide the full documentation (e.g. copy of diploma, contacts of referees).

Contact:

For more information please contact the PIs of the project Dr. Hao Li (Department of Geography) and A/P Filip Biljecki (Department of Architecture).

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