PhD Position in GIS and Remote Sensing for Peatland Research at NUS

 

Location: National University of Singapore (NUS), Department of Geography
Supervisors: A/P Massimo Lupascu & Asst. Prof. Hao Tang
Funding: MOE AcRF Tier 2 Grant

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Project Overview

We are seeking a highly motivated PhD candidate to join an interdisciplinary research project focused on understanding the impacts of seawater intrusion on Southeast Asian coastal peatlands. The project integrates field-based observations, remote sensing, and geospatial analysis to assess how saltwater intrusion affects peat degradation in coastal oil palm plantations on peat.

The candidate will work within a highly collaborative team, engaging with local and international partners and utilizing remote sensing technologies such as satellite imagery, and machine learning approaches.

Key Responsibilities

• Analyze historical land-use change using satellite images over project area
• Work with satellite datasets (e.g., Sentinel, Landsat, ALOS PALSAR) to monitor coastal environmental changes.
• Conduct fieldwork in Indonesia and Malaysia, including but not limited to soil and vegetation sample collection.
• Create high-resolution digital elevation model using UAV and/or other survey instruments.
• Develop models for peatland degradation detection, focusing on subsidence, elevation changes, and hydrological shifts.
• Collaborate with an interdisciplinary team, including experts in biogeochemistry and microbial ecology.

Essential Qualifications

• A Master’s degree (or equivalent) in Geography, Remote Sensing, GIS, or a related field.
• Strong proficiency in GIS, photogrammetry, and remote sensing analysis.
• Experience in satellite image processing, classification techniques, and spatial data analysis.
• Programming skills in Python, R, or MATLAB for geospatial data processing and machine learning applications.
• Willingness to conduct fieldwork in tropical environments and collaborate with international research teams.

Desirable Skills

• Experience with machine learning methods for land cover classification.
• Familiarity with peatland ecosystems, carbon flux modelling, or hydrological modeling.
• Previous work with LiDAR data for elevation and biomass estimation is a plus.

Funding & Benefits

• Full scholarship covering tuition and stipend for four years.
• Access to state-of-the-art remote sensing laboratories and fieldwork support.
• Opportunities to present at international conferences and publish in top-tier journals.

How to Apply

Interested candidates should send the following to Asst. Prof. Hao Tang [hao.tang@nus.edu.sg] and A/P Massimo Lupascu at [mlupascu@nus.edu.sg].

Please include:

1. Curriculum Vitae (CV) Detailing academic background and research experience.
2. Names and contact information of referees
3. Statement of Purpose (SOP) Your SOP should be no more than 2,100 words total, and must be divided into two parts:

a) Background and Motivation (maximum 600 words)

• Explain your reasons for applying to the PhD programme and your future career goals.
• Discuss how your educational, professional, and life experiences have shaped your decision to pursue a PhD.
• Include any relevant information that could help the admissions committee assess your motivation and aptitude. This may include:
  • Inspirational works or publications (use a consistent citation format)
  • Prior work such as your thesis, journal articles, conference presentations, or other academic outputs.

b) Research Proposal (maximum 1,500 words, including references)

• Propose how you would assess the impact of saltwater intrusion on peat degradation in coastal oil palm plantations.
• Describe the conceptual framework, methodological approach, and/or techniques you plan to use to structure and operationalize the research.
• Mention the name(s) of the NUS Geography faculty members you’ve consulted prior to submitting your application.
• Include references.

Application Deadline: 30th April 2025

Join us in pioneering research on tropical peatland conservation and climate resilience using cutting-edge geospatial science!