PhD Fellowship in Remote Sensing: The University of Copenhagen invites applications for a PhD fellowship focused on Earth Observation, utilizing advanced satellite remote sensing and deep learning (DL) algorithms. This fellowship is part of the TreeSense project at the Center for Remote Sensing and Deep Learning of Global Tree Resources, aiming to revolutionize monitoring of global tree resources and their role in climate regulation, biodiversity, and sustainability. The position offers full-time employment for up to 3 years, starting no earlier than 1st July 2025.
PhD Fellowship in Remote Sensing and Deep Learning – University of Copenhagen
Designation
PhD Fellow
Details
| Field | Details |
|---|---|
| Designation | PhD Fellow |
| Research Field | Remote Sensing, Deep Learning, Earth Observation |
| Location | Department of Geosciences and Natural Resource Management, University of Copenhagen, Denmark |
| Employment Start Date | 1st July 2025, but later start dates are possible |
| Duration | Full-time, up to 3 years |
| Application Deadline | 1st March 2025 |
Research Area
The research is part of the TreeSense project, which focuses on advanced deep learning techniques and satellite remote sensing (e.g., PlanetScope and Sentinel sensors). Key tasks include global-scale monitoring of tree resources, assessing structural and functional tree dynamics, and developing AI-powered approaches to analyze deforestation, forest degradation, carbon stocks, and sequestration rates.
Key areas of focus:
- Combining multi-source satellite data (e.g., PlanetScope, Sentinel-1/2) to enhance tree property assessment.
- Developing methods for monitoring disturbances and change dynamics at the single-tree level.
- Investigating the environmental, societal, and economic relevance of tree ecosystems.
Location
Department of Geosciences and Natural Resource Management, University of Copenhagen, Denmark.
Work includes an international research exchange stay and potential fieldwork in collaboration with global institutions in France, Spain, and China.
Eligibility/Qualification
Applicants must meet the following criteria:
- Requirements:
- Master’s degree equivalent to a Danish degree in relevant disciplines (e.g., geography, geoinformatics, Earth observation).
- Strong programming skills, particularly in Python.
- Fluency in written and spoken English.
- Preferred Skills:
- Experience in remote sensing, deep learning, and large satellite image datasets.
- Knowledge of AI-based techniques for image sharpening and super-resolution is advantageous.
- History of academic publication is a plus.
Job Description
The selected candidate will:
- Conduct independent research on global tree resource monitoring using AI and remote sensing techniques.
- Integrate PlanetScope and Sentinel satellite data for environmental analysis.
- Develop deep learning frameworks to enhance tree property assessment and sharpen image resolution.
- Collaborate with renowned international institutions in Europe and China.
- Participate in teaching duties and dissemination of findings through high-impact publications.
- Complete a PhD thesis based on the project.
How to Apply
Interested candidates must submit an online application in English via the University of Copenhagen’s portal. Include the following:
- A cover letter (max 2 pages) detailing background, qualifications, research interests, and motivation.
- A CV (max 2 pages).
- Relevant academic transcripts (BSc and MSc).
- Optional: Reference letters (1-3) and a brief abstract of MSc thesis (max 300 words).
Application Portal: University of Copenhagen Job Portal
Application Guidance: Visit the PhD School’s website for detailed eligibility information.
Last Date to Apply
1st March 2025, 23:59 GMT +1
Embark on an exciting journey to explore cutting-edge research and join one of Europe’s top universities as a PhD Fellow in Remote Sensing and Deep Learning.
