Publisher
source

Wageningen University & Research

Just Landed

PhD in Radar Remote Sensing for Detecting Logging in Tropical Forests Wageningen University & Research in Netherlands

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhD position with a tailored course program. Salary is €3,204 per month in the first year, rising to €4,051 per month in the fourth year, based on a 38-hour work week. Temporary contract for 18 months, extendable for the project duration if performance is good.

Deadline

Nov 17, 2026

Country flag

Country

Netherlands

University

Wageningen University & Research

Social connections

How do I apply for this?

Sign in for free to reveal details, requirements, and source links.

Apply for this position

Keywords

Computer Science
Environmental Science
Deep Learning
Biology
Forestry
Geography
Earth Science
Rainforest Ecology
Geostatistic

Suggested positions

About this position

Wageningen University & Research is advertising a fully funded PhD position on radar remote sensing for detecting logging in tropical forests. The project addresses illegal timber trade by developing scientific tools to detect logging activity and logging intensity across pantropical forests and to help verify claimed timber origin.

The PhD will work with novel satellite radar data, process and analyse remote-sensing datasets, develop and test methods for logging detection, and contribute to multi-authored publications and a PhD thesis. The research is embedded in the Forest Ecology and Forest Management group and the Laboratory of Geo-Information Science and Remote Sensing, within the Timtrace team. The project also involves international partners in Central Africa, South-East Asia, and South and North America, plus a user committee including authorities, timber industry, and NGOs.

Eligibility highlights include an MSc in Ecology, Environmental Science, Forest & Nature Conservation, Geo-Information Science, or a related field; proven experience in forest remote sensing; and strong analytical, collaborative, and communication skills. Experience with radar and optical satellite data and deep learning is an advantage. English proficiency at C1 level is expected.

The position is based at Wageningen University & Research in the Netherlands. The salary is €3,204 per month in year 1, rising to €4,051 per month in year 4, with a 38-hour work week and an 18-month contract extendable for the project duration. Applications are due 17 November 2026.

To apply, submit a CV (max. 2 pages) and motivation letter (max. 1 page) via the WUR vacancy page and complete the mandatory online form. Only applications submitted through the website will be considered.

Funding details

Fully funded PhD position with a tailored course program. Salary is €3,204 per month in the first year, rising to €4,051 per month in the fourth year, based on a 38-hour work week. Temporary contract for 18 months, extendable for the project duration if performance is good.

What's required

Applicants must have a successfully completed MSc degree in Ecology, Environmental Science, Forest & Nature Conservation, Geo-Information Science, or a related field. Proven experience in remote sensing of forests is required, and experience with radar and optical satellite data is an advantage. Experience with deep learning methods is also an advantage. Strong motivation for applied research, excellent analytical and critical thinking skills, collaborative and creative mindset, strong interpersonal and communication skills, and English at C1 level are expected; an internationally recognised English proficiency certificate may be required.

How to apply

Apply through the vacancy page on the WUR website using the apply button. Submit a CV of max. 2 pages and a motivation letter of max. 1 page; total documents must not exceed 3 pages. Also complete the mandatory online form linked in the post.

More information can be found here

Ask ApplyKite AI

Start chatting
Can you summarize this position?
What qualifications are required for this position?
How should I prepare my application?