Research Associate: ML for Earth Observation & Geospatial AI

Nanyang Technological University, Singapore (NTU Singapore); Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

NTU Singapore's School of Civil and Environmental Engineering seeks a Research Associate in Machine Learning for Earth Observation to develop self-supervised, temporal and multimodal models for satellite image time series and geospatial data. The role focuses on coastline change, land subsidence, urban expansion and vegetation monitoring.

You will explore vision–language and generative model directions, with access to high-performance GPU computing and close mentoring from the research group.

Qualifications

• Master's degree in a related field such as CS/EE/Remote Sensing/Geomatics/Civil and Environmental Engineering.
• Knowledge of machine learning and deep learning.
• Experience with remote sensing or geospatial data; SAR interferometry is a plus.
• Proficiency in Python and PyTorch on Linux/GPU computing; foundation models/vision–language models/AI agents are a plus.
• Good communication skills; able to work independently and in a team.
• Self-driven and interested in pursuing a PhD.

Responsibilities

• Develop deep learning models for satellite image time series and multimodal Earth observation data.
• Develop next generation geospatial foundation models, such as carbon minimization.
• Explore emerging ML methods for Earth observation, including vision–language and multimodal LLMs linking satellite data with text.
• Apply models to coastline change, land subsidence, urban expansion and vegetation monitoring.
• Build scalable, reproducible processing pipelines on HPC and cloud computing; maintain open-source code/datasets.
• Prepare data and reference labels, evaluate models, and maintain open-source code.
• Write papers and reports, present results, and support the research group.

Skills

Machine learning

Deep learning

Python

PyTorch

Remote sensing

Geospatial data

Communication skills

Teamwork

Self-driven

Education

Master's degree

Tools

GPU computing

Job description

NTU Singapore's School of Civil and Environmental Engineering seeks a Research Associate in Machine Learning for Earth Observation to develop self-supervised, temporal and multimodal models for satellite image time series and geospatial data. The role focuses on coastline change, land subsidence, urban expansion and vegetation monitoring.

You will explore vision–language and generative model directions, with access to high-performance GPU computing and close mentoring from the research group.