NATIONAL UNIVERSITY OF SINGAPORE

Research Fellow, Civil And Environmental Engineering

7 days left

Location
Singapore
Posted
19 Mar 2021
End of advertisement period
18 Apr 2021
Ref
3490344
Contract Type
Permanent
Hours
Full Time

Job Description

Applications are invited for multiple positions of Research Fellow (Postdoc) in the Department of Civil & Environmental Engineering at the National University of Singapore. The successful candidates are expected to be involved in a project titled ‘Advanced geological mapping using machine learning techniques’ that utilizes large data set of borehole samples. The National University of Singapore (NUS) is a leading global university; ranked 1st in Asia and 11th globally in the 2020 Quacquarelli Symonds (QS) World University Rankings, and the NUS Department of Civil & Environmental Engineering [www.eng.nus.edu.sg/cee] has been placed 9th internationally in Civil & Structural Engineering. According to USNEWS & World Report, NUS CEE ranked 3rd globally for Civil Engineering for 2020. According to USNEWS & World Report, NUS CEE ranked 3rd globally for Civil Engineering for 2020. 

Qualifications

For research fellow appointment, the successful applicant is expected to have a PhD degree, or be about to complete his or her PhD study in civil/geotechnical engineering, engineering geology, or any other relevant areas to the project (e.g., machine learning, data analytics, statistics, operations research). Specific guidelines are given below: - 

  • 2 postdoctoral research fellow with a strong background in geotechnical engineering, engineering geology, and/or rock mechanics. It is preferred that the individuals demonstrate appropriate knowledge in soil stratification and site investigation studies. Candidates who have no prior knowledge on machine learning/ data analytics can also apply the position. 
  • 2 postdoctoral research fellows with a strong background in machine learning, data analytics, and statistics. It is preferred that the individuals demonstrate prior knowledge of applying machine learning techniques for modelling spatial variability and have experience with computation with sizable data sets. Candidates who have no knowledge of geotechnical engineering/geology but who are interested in applying machine learning approaches to geological mapping can apply for this position. 

Good communication and team working skills with the ability to present research findings in publications and meetings are also required. The salary will depend upon research experiences. Only short listed applicants will be notified. 

More Information

Location: Kent Ridge Campus
Organization: Engineering
Department : Civil And Environmental Engineering

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