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Abdulhakim M. Abdi

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Postdoctoral Researcher in Forest Remote Sensing and Climate Risk Assessment Lund University in Sweden

Degree Level

Postdoc

Field of study

Computer Science

Funding

Two-year postdoctoral position. No stipend amount or additional funding details are stated in the post.

Deadline

Sep 27, 2026

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Country

Sweden

University

Lund University

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Keywords

Computer Science
Environmental Science
Biology
Geography
Spatial Analysis
Earth Science
Python Programming
Earth Observation
Statistics
Drought
Climate Risk
ML

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About this position

Postdoctoral Researcher in Forest Remote Sensing and Climate Risk Assessment at Lund University, Sweden.

This postdoctoral opening is in the Department of Earth and Environmental Sciences (MGeo), Lund University. The project focuses on forest remote sensing, climate risk assessment, and Earth observation, using Landsat and Sentinel time series together with machine learning to study major climate-related risks facing Swedish forests.

Research themes include drought stress, storm damage, bark-beetle susceptibility, drought-induced mortality, windthrow, and outbreak dynamics. A major part of the work will be developing the research into a monitoring system, so the role combines scientific analysis with applied environmental monitoring.

Ideal candidates should have a strong background in remote sensing, geospatial analysis, Python, and machine learning, with experience handling large Earth observation datasets preferred. The poster specifically asks applicants to read the vacancy announcement carefully and ensure their background matches the stated requirements before applying.

This is a two-year postdoctoral position. The application deadline is 27 September 2026. The full announcement and application portal are available via the linked vacancy page.

Institution: Lund University. Location: Sweden.

Funding details

Two-year postdoctoral position. No stipend amount or additional funding details are stated in the post.

What's required

Applicants should have a strong background in remote sensing, geospatial analysis, Python, and machine learning, ideally with experience working with large Earth observation datasets. The post emphasizes disciplinary fit for a specialized postdoctoral position in remote sensing and environmental science.

How to apply

Read the vacancy announcement carefully, then apply through the full announcement/application portal. Ensure your background matches the stated requirements before submitting an application or contacting the poster.

More information can be found here

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