PhD fellowship in Machine Learning for Environmental Sciences – Department of Computer Science, Machine Learning Section Full-time

Fully-funded PhD Fellowship in Machine Learning

The Department of Computer Science, Machine Learning Section, invites applications for a fully-funded PhD fellowship. The position is part of the Global Wetland Center (GWC), funded by the Novo Nordisk Foundation. The start date is July 01, 2026 or as soon as possible hereafter. The submission deadline is April 06, 2026.

About the Global Wetland Center

The GWC contributes to the development of wetland-based climate change mitigation strategies through a combination of biogeochemical and hydrological modelling, satellite remote sensing and use of artificial intelligence techniques. The center is a collaboration between two departments from the University of Copenhagen (Department of Geosciences and Natural Resource Management and Department of Computer Sciences), DHI A/S, and GEUS (The Geological Survey of Denmark and Greenland).

About the PhD Position

We are looking for a creative student who is interested in contributing to the mission of the GWC, by developing novel machine learning methods to model greenhouse gas fluxes from both remotely sensed multimodal data and ground-level measurements. To overcome challenges of limited reference data, the student will work on hybrid modelling combining process-based models and deep learning, as well as self-supervised learning approaches. The PhD student will contribute to the development of new global scale datasets.

Applicants must hold an equivalent to a Danish master's degree in computer science, applied mathematics, geomatics, or related disciplines. The position requires genuine interest in interdisciplinary research and a strong background in machine learning and computer vision. The student will work on high-impact research projects with a focus on methodological research targeting top-tier computer science publication venues (NeurIPS, CVPR, ICML, ICCV, ECCV, etc.) and journals in remote sensing and ecology.

Experience in working with different remote sensing modalities is required, as well as programming experience in Python (especially PyTorch, GDAL, Rasterio, GeoPandas). Knowledge in differentiable programming is a plus.

The PhD student will collaborate closely with researchers at the Global Wetland Center and will also be affiliated with the Danish Pioneer Center for AI. Depending on the candidate, there is an option to become part of the ELLIS PhD program.

Principal Supervisor

ELLIS fellow Prof. Christian Igel, igel@di.ku.dk, DIKU. Co-supervisor is Assistant Prof. Nico Lang, nila@di.ku.dk, from DIKU.

Our Section and Research – and What Do We Offer?

The Machine Learning Section is a part of the Department of Computer Science, Faculty of SCIENCE, University of Copenhagen, and the ELLIS Unit Copenhagen. The University of Copenhagen was founded in 1479 and is the oldest and largest university in Denmark. It is ranked as the best university in Scandinavia and as one of the top institutions in Europe. The university is hosting the Pioneer Center for Artificial Intelligence.

The Department of Computer Science (DIKU) offers a friendly and thriving international research and working environment with opportunities to build up internationally competitive research groups. Copenhagen is one of the 10 most livable cities in the world with a rich culture within music, theater and associations. Life for families is made easy by a publicly supported daycare and health care system, dual career opportunities, maternity/parental leave and six weeks of paid annual vacation. International candidates may find information on living and working in Denmark here. Useful information is also available at The International Staff Mobility office (ISM) at the University of Copenhagen (link). ISM offers a variety of services to international researchers coming to and working at the University of Copenhagen.

The PhD Programme

Qualifications needed for the regular programme include having 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. Computer Science, Electrical Engineering, Mathematics, Operations Research, and Statistics. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database.

Terms of employment in the regular programme include full-time employment for a maximum of 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.

Salary, pension and terms of employment are in accordance with the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State. Depending on seniority, the monthly salary starts at approximately 31,242 DKK/Roughly 4,180 EUR (November 2025 level) plus pension. The position is covered by the Protocol on Job Structure.

Responsibilities and Tasks in Both PhD Programmes

1. Complete and pass the MSc education in accordance with the curriculum of the MSc programme (ONLY when you are attending the integrated MSc and PhD programme)

2. Carry through an independent research project under supervision

3. Complete PhD courses corresponding to approx. 30 ECTS / 1⁄2 FTE

4. Participate in active research environments, including a stay at another research institution, preferably abroad

5. Teaching and knowledge dissemination activities

6. Write scientific papers aimed at high-impact journals

7. Write and defend a PhD thesis on the basis of your project

We Are Looking for the Following Qualifications

1. Professional qualifications relevant to the PhD project

2. Strong interest in the relevant topics

3. Academic background (e.g. courses taken) in the relevant topics

4. Good English language skills

5. (Optional) Relevant publications

6. (Optional) Relevant work experience

Application and Assessment Procedure

Your application including all attachments must be in English and submitted electronically by clicking 'Apply for position'.

Please include:

1. Motivated letter of application clearly mentioning the project you are applying for (max. two pages)

2. Curriculum vitae including information about your education, experience, relevant courses, language skills, names and email addresses of three referees, and other skills relevant for the position

3. Original diplomas for Bachelor of Science or Master of Science 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.

4. Publication list (if possible)

5. Remember to indicate the name of Principal Supervisor in the application!

Application Deadline

The deadline for applications is April 06, 2026. 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 the 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 shortly after the submission deadline.

Questions

For specific information about the PhD fellowship, please contact the relevant supervisors whose emails are provided above.

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