PhD fellowships in Remote Sensing and Deep Learning for understanding woody ecosystem response to climate change Full-time

PhD Fellowships In Remote Sensing And Deep Learning For Understanding Woody Ecosystem Response To Climate Change

The Department of Geosciences and Natural Resource Management invites applicants for two PhD fellowships in Remote Sensing and Deep Learning for understanding woody ecosystem response to climate change. The PhD positions are 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 June 2026, but later start dates are possible.

The TreeSense Center 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 will 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 PhD scholarships will be part of a research theme aiming at improving our current knowledge on how climate change affects woody resources by generating annual global high-resolution satellite-based datasets including a wide range of woody properties assessed at the level of single trees and quantified at tree- or patch-level (e.g. tree count, forest structure complexity, biomass or species diversity).

The role of the PhD students will be to develop research techniques for an improved characterisation of changes in global woody ecosystem functioning and structure as well as an improved understanding of woody ecosystem responses to global environmental change in a warming world. This includes characterization of selected relevant tree species distributions at species or genus level, which could ideally leverage the basis for developing new methods to better understand woody ecosystem resilience and vulnerability to climate change impacts. Output predictions are expected to be based on existing networks and databases of relevant ground observations, sub-meter resolution satellite training data or coarse resolution labels of existing satellite-based products.

Scholarship One is expected to focus primarily on developing deep learning technical methods for improved characterization and understanding of global woody ecosystems changes and scholarship Two will focus more on the “applied dimension” relating the remotely sensed information of global woody ecosystems changes to climate change/ecology/geoscience aspects. Please indicate in the proposal your preference for one or two (or equally interested).

The PhD scholarships include 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.

Main Supervisors are Associate Prof. Martin Brandt, mabr@ign.ku.dk (scholarship One) and Professor, Rasmus Fensholt, rf@ign.ku.dk (Scholarship Two), Department of Geoscience and Natural Resource Management. Co-supervisors are Co-PIs Assistant Prof. Ankit Kariryaa and Professor Christian Igel, Department of Geoscience and Natural Resource Management/Department of Computer Science and the two international Center Co-PIs, Philippe Ciais (LSCE France) & Josep Peñuelas (CREAF Spain).

We are seeking highly motivated scholars 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.

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

The PhD programme A three year full-time study within the framework of the regular PhD programme (5+3 scheme), if you already have an education equivalent to a relevant Danish master's degree. 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

We are looking for the following qualifications:

• Professional qualifications relevant to the PhD project
• Relevant publications
• Relevant work experience
• Other relevant professional activities
• Curious mind-set with a strong interest in how remote sensing and AI can be used to assist in reaching the global sustainable development goals like SDG 13 (Climate Action) and 15 (Life on Land).
• Good language skills

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)
• Original diplomas for Bachelor or Master and transcript of records in the original language, including an authorized English translation if issued in another language than English or Danish. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted.
• 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 March 15th 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 in early/mid-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.