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PhD Stipend in Anomaly Detection for Future Urban Cooling Systems

Aalborg Universitet (AAU)



PhD Stipend in Anomaly Detection for Future Urban Cooling Systems

Jobbeskrivelse
The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of Anomaly Detection for Future Urban Cooling Systems within the general study programme Electrical and Electronic Engineering; as per September 1, 2026, or as soon as possible thereafter.

In electronic engineering, Aalborg University is known worldwide for its high academic quality and societal impact. The Department of Electronic Systems employs more than 200 people, of which about 90 are PhD students, and about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and results into applications in close collaboration with industrial partners worldwide. You can read more about the department at www.es.aau.dk.

Your work tasks
Applications are invited for a three year PhD position focused on anomaly detection and fault diagnosis in large-scale cooling systems for future mega-cities. The position is part of the SWiM project, an international collaboration involving Aalborg University, Aarhus University , Nanyang Technological University, and Grundfos company.

The energy demand for cooling is growing faster than any other end use in the building sector, having more than tripled between 1990 and 2016. As cities expand and urban heat intensifies, efficient and reliable cooling infrastructure becomes critical. Yet current systems suffer from persistent challenges: design oversizing leads to inefficient operating points, poor maintenance causes equipment degradation and energy waste, and sloppy or absent commissioning results in poor system balance and underutilized energy-saving potential. Detecting and diagnosing these faults early at the component, building, and city-district level is essential for the sustainable cities of tomorrow.

This PhD project addresses a fundamental challenge in modern urban energy infrastructure: the intelligent, automated monitoring and management of large-scale cooling systems spanning components, buildings, and urban districts. As cooling systems grow in complexity and scale, traditional monitoring approaches are insufficient to ensure efficient, reliable, and fault-free operation. This project will develop novel AI methods that bridge first-principles physical knowledge with data-driven learning to enable continuous, autonomous system oversight.

Research objectives
The project pursues two interconnected research directions:

    • Continuous commissioning and adaptive control. The PhD candidate will develop methods for the ongoing, automated adjustment of controllers, sensors, actuators, and associated control hardware. Rather than one-time commissioning at installation, the system will continuously recalibrate itself in response to changing operating conditions. Reinforcement learning is envisaged as the primary methodological vehicle, enabling the system to learn optimal adjustment policies directly from interaction with the physical infrastructure.
    • Anomaly detection and fault diagnosis. The candidate will develop a multi-level diagnostic framework spanning three scales: individual components, building-level systems, and urban district networks.
    The framework will integrate complementary approaches:

    1) Physics-informed and data-driven AI methods for efficiency monitoring and fault detection, combining sensor data, system layout knowledge, and physical principles to extract spatial-temporal features and predict equipment behaviour;

    2) Statistical anomaly detection to identify and characterise deviations from normal system operation in a principled, probabilistic manner.

    Your competencies
    We are looking for a motivated candidate with:

    • A Master's degree in electrical engineering, control engineering, applied mathematics, computer science, or a related field
    • A strong background in probability and statistics, machine learning, or control theory
    • Interest in cyber-physical systems, energy systems, or smart buildings
    • Good programming skills (Python, MATLAB, or similar)
    • Excellent communication skills in English

    Who we are
    The PhD Fellow will be affiliated with the Learning and Decisions research group. Our goal is to enable machines and infrastructures to operate autonomously, work together, and collaborate with people. We develop new artificial intelligence methods to make infrastructures and production more effective and energy-efficient, with algorithms that autonomously learn the behaviour of technical and socio-technical systems and make optimal decisions without human intervention. Applications range from robotics to water infrastructures, using optimisation techniques that must be safe to operate, hence our focus on safety.

    Qualification requirements
    PhD stipends are allocated to individuals who hold a Master's degree. PhD stipends are normally for a period of 3 years. It is a prerequisite for allocation of the stipend that the candidate will be enrolled as a PhD student at the Technical Doctoral School of IT and Design in accordance with the regulations of Ministerial Order No. 1124 of September 19, 2025 on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions. According to the Ministerial Order, the progress of the PhD student shall be assessed at regular points in time. As part of the PhD study, you are among other things required to complete PhD courses corresponding to 30 ECTS, gain experience with teaching or other forms of knowledge dissemination and complete an external research stay outside of Aalborg University, preferably 3-6 months at a foreign research institution.

    How to apply
    Your application must include the following:

    • Application, stating reasons for applying and qualifications in relation to the position,
    • Curriculum Vitae (CV)
    • Diplomas (bachelor and master's degree diploma)
    • Research vision and ideas for the Project: Applicants are encouraged to include their own suggestions and ideas for how they envision approaching the research within this project
    • Other relevant documents

    The application must be submitted via Aalborg University’s recruitment system, which can be accessed under the job advertisement on Aalborg University's website.

    Aalborg University wants to reflect the surrounding society and has diversity as a core value. Therefore, everyone, regardless of personal background and orientation, is encouraged to apply for the position.

    Do you have any questions?
    If you have any questions about the position, you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost.

    Further information
    Read more about our recruitment process here.

    The assessment of candidates for the position will be carried out by qualified experts.
    Shortlisting will be applied. This means that after the application deadline, the head of the department, with the assistance of the hiring committee, will select the applicants to be assessed. All applicants will be informed whether they have been shortlisted for assessment or not.

    The hiring process at Aalborg University may include a risk assessment as a tool to identify potential risks associated with new hires, ensuring the safety, compliance, and integrity of the workplace.

    Read more about The Technical Doctoral School of IT and Design

    Salary and terms of employment
    The employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities (the Appointment Order) and the Ministerial Order on Job Structure for Academic Staff at Universities (in Danish).

    Salary and terms of employment are in accordance with the collective agreement between the Danish Confederation of Professional Associations and the state (AC collective agreement) (in Danish)

    Aalborg University - Knowledge for the world
    Aalborg University is an international workplace with more than 3,700 employees. We offer real-world-oriented education and create world-class research results through collaboration between researchers, students, and public and private companies. This is how we achieve insights, new solutions to societal problems, and knowledge that changes the world. Our main campus is in Aalborg, but we also have campuses in Esbjerg and Copenhagen.

    Contacts

    Ansøgningsfrist
    19-07-2026

    Ref. nummer
    2026/860

    Afdeling
    Department of Electronic Systems

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    Ansøgningsfrist d. 01.09.2026
    NewTech & AI
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