Research Assistant Position – Carbon Stock Estimation Project

Research Assistant Position – Carbon Stock Estimation Project

Department: Center for Environmental Intelligence (CEI)

Location: VinUniversity, Hanoi, Vietnam

About Carbon Stock Estimation Project:

In this research, we intend to develop a new carbon stock estimation technique using satellite and drone imagery data integrated with machine learning and deep learning models. The aim is to create a robust methodology that can provide accurate and up-to-date information on carbon stock quantity over the forests in Vietnam. This approach will help in better understanding the carbon sequestration potential of forests, monitoring deforestation and forest degradation, and ultimately supporting this country to benefit most from the fast-growing carbon credit market. In the context of carbon credit, the targeted new level of accuracy of carbon stock estimation by this project will help in ensuring the credibility and effectiveness of carbon offset projects and verify the legitimacy of emission reduction claimed by projects. In addition, it will help enhance the integrity of the carbon credit market, enabling investors to make informed decisions, and driving sustainable investment in emission reduction initiatives.

Scope of Work:

We are seeking a motivated and qualified Research Assistant to join our research team working on a carbon stock estimation project using remote sensing, image processing, artificial intelligence, and deep learning.

Key Responsibilities:

The successful candidate will contribute to:

• Processing and analyzing satellite and remote-sensing imagery.

• Developing AI and deep learning models for forest and carbon stock estimation.

• Implementing image preprocessing, feature extraction, and data-fusion methods.

• Training, validating, and evaluating deep neural networks.

• Preparing technical reports, research documentation, and scientific publications.

• Collaborating with researchers, students, and external project partners.

Requirements:

Applicants should have:

• A bachelor’s or master’s degree in electrical engineering, Computer Science, Data Science, or a closely related field.

• Extensive background in image processing, artificial intelligence, and deep learning neural networks.

• Experience with Python and common deep learning frameworks such as PyTorch or TensorFlow.

• Strong analytical and problem-solving skills.

• Ability to work independently and as part of a multidisciplinary research team.

• Good written and verbal communication skills in English.

Experience in remote sensing, satellite image analysis, geographic information systems, or environmental applications is an advantage.