PhD fellowship in Remote Sensing and Deep Learning

The Department of Geosciences and Natural Resource Management invites applicants for a PhD fellowship in Earth Observation using state-of-the-art satellite remote sensing systems. The PhD position is part of Center for Remote sensing and Deep Learning of Global Tree Resources funded by the Danish National Research Foundation, which focuses on the critical role of trees in terrestrial ecosystems, such as climate regulation, biodiversity support, and local livelihoods.

Earliest start date is 1 July 2025, but later start dates are possible.

The TreeSense project

The research center aims to revolutionize global tree monitoring using advanced nano-satellite technology and next-generation deep learning (DL) methods within AI. This approach will enable detailed assessment of global tree dynamics, including key functional and structural properties such as important species, the use of trees, tree horizontal and vertical structure, carbon stocks and carbon sequestration rates.

This research paves the road towards addressing science questions on major unknowns within global change research. Here the center will break new grounds on how global warming and increased climatic extreme events affect tree physiology and growth patterns at species level and we will quantify the extent and dynamics of anthropogenic forest disturbance and degradation.

Ultimately, this research enable us to uncover the potentials for various forest and tree-related production systems and human livelihoods as means of climate mitigation actions while improving our understanding of the importance of woody resources for sustainable food systems.

The role of the PhD student will be to develop research techniques for improved assessment and monitoring of woody vegetation ecosystem properties at the level of single trees based on relevant remote sensing technology and AI algorithms, with a focus on disturbances and change dynamics. Specifically, the work will integrate both PlanetScope and Sentinel sensors using deep learning techniques. Our group has access to large amounts of PlanetScope data and has developed advanced methods for global-scale applications within environmental resource monitoring. However, the harnessing of model predictions by integrating freely available Sentinel-1 and Sentinel-2 data, as well as available snapshots of sub-meter resolution images, represents an exciting research avenue towards improved tree monitoring capabilities in time and space. The topic is flexible, but may include (guided) super-resolution or other image sharpening techniques. 

The PhD scholarship includes an international research exchange stay and the potential for conducting fieldwork in relevant case areas. Research partners are LSCE in France and CREAF in Spain, as well as several Chinese universities.

Principal supervisor is Associate Prof. Martin Brandt, mabr@ign.ku.dk Department of Geoscience and Natural Resource Management. Co-supervisors are Professor, Rasmus Fensholt, rf@ign.ku.dk and Assistant Prof. Ankit Kariryaa ak@di.ku.dk Department of Geoscience and Natural Resource Management/Department of Computer Science.

Who are we looking for?

We are seeking a highly motivated scholar with good interpersonal and communication skills. Fluency in spoken and written English is a requirement. As criteria for the assessment, emphasis will also be laid on Python programming skills and relevant experience in remote sensing and deep learning. Experience with handling and processing large image datasets and scientific publications are an advantage. Prior experience with remote sensing of tree resources is considered an advantage but is not formal a requirement.

Our group and research- and what do we offer?

Your work place will be the Department of Geosciences and Natural Resource Management (IGN), which conducts research and education on the past, present and future physical, chemical and biological environments of the Earth and their interactions with societal and human systems to provide graduates and research in support of sustainable future solutions for society. The department has strong experience in interdisciplinary collaboration within and beyond the department.

The PhD student will be part of the the TreeSense Center and also the exsisting remote sensing community together forming a large team of 20+ PhD students, postdocs and junior/senior scientists.

Further information on the Department can be found at https://ign.ku.dk/english/.

The PhD programme

To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. geography, earth observation, geoinformatics. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database.

Terms of employment in the regular programme
Employment as PhD fellow is full time and for maximum 3 years.

Employment is conditional upon your successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

Terms of appointment and payment accord to the agreement between the Danish Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State. The position is covered by the Protocol on Job Structure.

Responsibilities and tasks in the PhD programme

• Carry through an independent research project under supervision

• Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
• Participate in active research environments, including a stay at another research institution, preferably abroad
• Teaching and knowledge dissemination activities
• Write scientific papers aimed at high-impact journals
• Write and defend a PhD thesis on the basis of your project

Application and Assessment Procedure

 Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include: 

• A cover letter (max 2 page) describing your background, personal qualities, research interest and motivation for applying for this position, as well as an outline of research ideas for the position
• CV (max 2 pages)
• Diploma and transcripts of records (BSc and MSc)
• Other information for consideration, e.g. list of publications (if any)
• A short abstract of the MSc Thesis (max. 300 words)
• 1-3 reference letters (if any)

Application deadline: The deadline for applications is 1st of March 2025 23:59 GMT +1.

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process
After deadline, a number of applicants will be selected for academic assessment by an unbiased expert assessor. You are notified, whether you will be passed for assessment.

The assessor will assess the qualifications and experience of the shortlisted applicants with respect to the above mentioned research area, techniques, skills and other requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.

Interviews with selected candidates are expected to be held during the first two weeks of April.

Questions
For specific information about the PhD fellowship, please contact the principal supervisor.

General information about PhD study at the Faculty of SCIENCE is available at the PhD School’s website: https://www.science.ku.dk/phd/.

The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position.