National University of Singapore (NUS) Jobs

National University of Singapore (NUS)

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Kent Ridge Campus

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"Research Fellow (Water Resources)"

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Research Fellow (Water Resources)

Postdoctoral Research Fellow

2026-05-16

Location

Kent Ridge Campus

National University of Singapore

Type

Fixed-term contract

Required Qualifications

PhD in water resources engineering or related
Statistical modelling & extreme value analysis
Machine learning (neural networks)
Climate data analysis & stochastic simulation
Strong publication record (advantageous)

Research Areas

Stochastic climate emulators
Hydro-climatic processes
Extreme events
Data-driven analysis
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Research Fellow (Water Resources)

Job Descriptions

The Department of Civil and Environmental Engineering (CEE) at the National University of Singapore (NUS) is recruiting a post-doctorate Research Fellow. The successful candidate is required to work on developing stochastic climate emulators for statistical modelling and data-driven analysis of hydro-climatic processes and extreme events.

Job Requirements

  • Possess a recognised PhD degree in water resources engineering or a related discipline.
  • Strong written and communication skills.
  • Should have strong expertise in statistical modelling, extreme value analysis, and machine learning methods (e.g., neural networks), as well as experience in climate data analysis, stochastic simulation, or coastal and ocean modelling.
  • Familiarity with copula methods, surrogate modelling, or uncertainty analysis for environmental systems will be advantageous.
  • Have a good publication record is advantageous.
  • Only shortlisted applicants will be notified.
  • Open to fixed term contract.

More Information

Location: Kent Ridge Campus

Organization: College of Design and Engineering

Department: Civil and Environmental Engineering

Employee Referral Eligible: No

Job requisition ID: 32059

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Frequently Asked Questions

🎓What qualifications are required for this Research Fellow position at NUS?

Candidates must possess a recognised PhD in water resources engineering or a related discipline. Strong written and communication skills are essential. Expertise in statistical modelling, extreme value analysis, and machine learning methods (e.g., neural networks) is required, along with experience in climate data analysis, stochastic simulation, or coastal/ocean modelling. Familiarity with copula methods, surrogate modelling, or uncertainty analysis is advantageous. A good publication record helps. Explore more postdoc opportunities or research jobs for similar roles.

🔬What is the main research focus of this Water Resources Research Fellow role?

The role involves developing stochastic climate emulators for statistical modelling and data-driven analysis of hydro-climatic processes and extreme events in the Department of Civil and Environmental Engineering at NUS. Check related advice on thriving as a postdoc.

📝How do I apply for this Postdoctoral Research Fellow position?

Only shortlisted applicants will be notified. Apply directly via the job requisition ID 32059 on the NUS portal. Prepare your CV highlighting PhD, publications, and relevant expertise. Visit free resume templates and cover letter templates to strengthen your application for academic jobs.

🌍Is visa sponsorship available for international applicants?

Visa sponsorship is not mentioned in the job posting. Confirm directly with NUS HR during application. International researchers often explore postdoc positions with potential support in Singapore.

🏢What is the employment type and location for this role?

This is open to a fixed-term contract at the Kent Ridge Campus, National University of Singapore, in the College of Design and Engineering. Employee referrals are not eligible. Learn about university jobs in Singapore.

💻What advantageous skills can boost my application?

Familiarity with copula methods, surrogate modelling, or uncertainty analysis for environmental systems, plus a strong publication record, will be advantageous. Build skills via research assistant tips adaptable to postdocs.

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