Earth Observation ML Research Associate

Nanyang Technological University; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

NTU School of Civil and Environmental Engineering seeks a Research Associate in Machine Learning for Earth Observation to build self-supervised, temporal, and multimodal models for satellite image time series and geospatial data. The role involves exploring vision–language models, AI agents, and generative approaches, with access to GPU computing and close supervision.

The successful candidate will apply methods to coastline change, land subsidence, urban expansion and vegetation monitoring,

Qualifications

• Master's degree in a related field.
• 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; knowledge of foundation models/vision–language models or AI agents is 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 methods in machine learning for Earth observation, such as vision–language and multimodal large language models that link satellite data with text, agentic AI workflows that plan and carry out geospatial analyses, and generative models for data synthesis.
• Apply the models to coastline change, land subsidence, urban expansion and vegetation monitoring.
• Build scalable and reproducible processing pipelines on high-performance and cloud computing and maintain open-source code and 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

Communication

Independent work

PhD pursuit

Education

Master's degree in CS/EE/Remote Sensing/Geomatics/Civil & Environmental Eng or related field

Tools

Python

PyTorch

Job description

NTU School of Civil and Environmental Engineering seeks a Research Associate in Machine Learning for Earth Observation to build self-supervised, temporal, and multimodal models for satellite image time series and geospatial data. The role involves exploring vision–language models, AI agents, and generative approaches, with access to GPU computing and close supervision.

The successful candidate will apply methods to coastline change, land subsidence, urban expansion and vegetation monitoring,