PhD scholarship in Cutting-Edge Machine Learning Methods for Climate Modelling

Do you want to do research on cutting-edge machine learning methods for climate modelling?

If you are establishing a career as a researcher in machine learning and are motivated to work with the latest generative models for climate modelling, we can offer you a strong foundation. We seek a highly motivated and talented PhD student to join our group at DTU Compute, offering a fully funded PhD scholarship (3-year employment) in a vibrant interdisciplinary research environment. 

The position is part of the research project "IcyAlert - Intelligent Climate Early Warning Alert for Arctic Ice-Free Summers" , funded under the NNF Grand AI Challenge programme. 

You will become part of an enthusiastic team working closely with collaborators at DMI (Danish Meteorological Institute) and RMI (Royal Meteorological Institute of Belgium) to advance neural network-based methods for climate modelling. 

About IcyAlert 

The goal of the IcyAlert project is to provide robust predictions of Arctic ice-free summers at multi-seasonal time scales and their potential climate impacts under various warming scenarios, supporting sustainable climate solutions. Arctic summer sea ice extent has declined by nearly 13% per decade since 1979, accompanied by a 90% reduction of older ice. These changes pose increasing risks to ecosystems, food security, navigation, etc. 

By combining dynamical models, satellite data, causal analysis, and explainable AI, IcyAlert will identify critical thresholds, enhance prediction accuracy, and generate automated alerts for seasonal Arctic and extratropical climate events. Using Gefion in the project will be essential for analysing complex datasets and training advanced large-scale predictive models. This interdisciplinary initiative brings together experts in AI, climate modelling, and causal analysis to enhance preparedness for an ice-free Arctic. 

Responsibilities and qualifications 

This PhD project will focus on reducing uncertainties in Arctic sea-ice predictions. There will be three subprojects: 1) develop a climate data retrieval system in close collaboration with researchers at DMI and RMI. The pipeline is based on CMIP6, CMIP7, and C3S data. 2) develop generative AI models that can create high-resolution climate data based on low-resolution input, 3) develop probabilistic AI models to generate ensembles of Arctic winter initial states, which will be used as input to physical climate simulations to explore predictive relationships across warming scenarios. 

You should have the following required skills: 

• Demonstrated experience in deep learning, including some exposure to graph neural networks or diffusion models. 
• Proven experience with implementing machine learning methods in Python and Pytorch or Flax.
• Familiarity with managing a larger code base and training models on HPC systems. 
• Familiarity with climate modelling is a plus. 
• High level of motivation and creative problem-solving skills. 
• Excellent communication and writing skills in English.

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment 

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education. 

Assessment

The assessment of the applicants will be made by Associate Professor Tommy Sonne Alstrøm. 

We offer

DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms 

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. 

The period of employment is 3 years. Starting date is 1 February 2026 (or according to mutual agreement). The position is a full-time position. 

You can read more about career paths at DTU here.

Further information 

Further information may be obtained from Associate Professor Tommy Sonne Alstrøm,

You can read more about DTU Compute at  

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar "PhD relocation to Denmark and startup "Zoom" seminar" for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. 

Application procedure 

Your complete online application must be submitted no later than 8 December :59 Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae 
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it. 

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

DTU Compute
DTU Compute – Department of Mathematics and Computer Science – is an internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our research results contribute to creating a better society by supporting areas such as health, green transition, energy supply, and life science. We collaborate with universities, public and private organisations, and companies in Denmark and abroad, and through DTU's startup ecosystem, we encourage innovation and entrepreneurship. We have a strong ethical, human, and sustainable approach that ensures integrity in our work. Therefore, we strive for and take responsibility for driving the democratisation of digital technologies, so that everyone has the opportunity to actively participate in the development, and we ensure a continued open, democratic, and inclusive society for the benefit of all. At DTU Compute, we value diversity, inclusion, and a flexible work-life balance. Read more about us at 

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN's 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.