PhD Stipend: Learning the Structure and Dynamics of Complex Networks in Ecological Systems (AI:EcoNet Lab, Aalborg University) Aalborg University in Denmark

The AI:EcoNet Lab at Aalborg University, part of the AI:X initiative, offers a fully funded PhD stipend focused on advancing artificial intelligence research through interdisciplinary collaboration. The lab is a joint effort between the Department of Computer Science and the Department of Chemistry and Bioscience, and is one of five labs established in 2025 under the AI:X umbrella, collectively offering 20 PhD stipends. This particular position is open for appointment from October 1, 2026, or soon thereafter, and has a duration of three years.

The research project centers on learning the structure and dynamics of complex networks, with a primary application to ecological systems. Species interact in intricate biological networks, such as food webs, which underpin natural ecosystems. However, predicting how these networks change over time and space remains a challenge, especially as human activities increasingly threaten species and ecosystem functionality. The AI:EcoNet Lab aims to develop novel graph representation learning models to understand and predict interactions in dynamic ecological networks, contributing to both fundamental science and real-world impact.

The successful PhD candidate will work on representation learning methods for graphs, modeling both static and temporal networks. The project emphasizes scalable approaches to capture network evolution, with applications extending beyond ecology. Candidates will collaborate closely with other lab members and benefit from the interdisciplinary environment.

Eligibility and Requirements: Applicants must hold a Master’s degree in computer science, mathematics, statistics, physics, or a related field. A strong background in machine learning is essential, preferably with experience in probabilistic modeling, Bayesian machine learning, or graph representation learning. Programming skills in Python and familiarity with deep learning frameworks such as PyTorch are required. Interest in ecological or biological networks, strong analytical and communication skills, and proficiency in written and spoken English are mandatory. Enrollment as a PhD student at the Technical Doctoral School of IT and Design is a prerequisite, and candidates must complete PhD courses (30 ECTS), gain teaching or dissemination experience, and undertake an external research stay (preferably 3-6 months) outside Aalborg University.

Funding and Employment: The position is fully funded, with salary and terms of employment governed by the collective agreement between the Danish Confederation of Professional Associations and the state (AC collective agreement). There is a mutual probationary period of three months. The employment follows the Ministerial Order on the Appointment of Academic Staff at Universities and the Job Structure for Academic Staff at Universities.

Application Process: Applications must be submitted via Aalborg University’s recruitment system. Required documents include a cover letter (detailing motivation and research interests), CV, grade transcripts and diplomas (in English), contact information for references, and a publication list if available. The university values diversity and encourages applications from all backgrounds. The selection process involves shortlisting and assessment by qualified experts, with all applicants informed of their status. Interviews are expected to take place between August 10 and 21.

About Aalborg University: Aalborg University is an international institution with over 3,700 employees, offering real-world-oriented education and world-class research. The main campus is in Aalborg, with additional campuses in Esbjerg and Copenhagen. The university fosters collaboration between researchers, students, and industry partners to address societal challenges and generate impactful knowledge.

For scientific inquiries, contact Assistant Professor Abdulkadir Celikkanat at [email protected]. For further information about the recruitment process and the Technical Doctoral School of IT and Design, refer to the university’s website.