PhD Stipend in Real-time Stream Data Analysis for Wind Turbine Monitoring – Electrical and Electronic Engineering Aalborg University in Denmark

The Department of Electronic Systems at Aalborg University is offering a PhD stipend in Real-time Stream Data Analysis within the Electrical and Electronic Engineering study programme, starting August 1st, 2026 or as soon as possible thereafter. Aalborg University is internationally recognized for its high academic standards and societal impact, particularly in electronic engineering. The Department of Electronic Systems employs over 200 staff, including 90 PhD students, and is known for its diverse, international environment and problem-based learning model.

This PhD project addresses the data-intensive challenges of modern wind turbine testing and verification. Wind turbines, especially prototypes, generate vast amounts of high-frequency telemetry data (vibration and acoustic signals sampled at tens of kilohertz) in remote locations with unreliable communication channels. The research aims to develop reliable, resilient, and performant machine learning solutions for efficient transmission and analysis of high-frequency, multimodal data streams, enabling critical-event monitoring of offshore wind turbines. Key objectives include:

• Edge intelligence: Developing smart algorithms for on-turbine data preprocessing.
• Resilient data movement: Creating error-tolerant, cybersecure, standards-compliant communication layers to mitigate data corruption and synchronize high-rate sensor streams.
• Inference generalization: Extrapolating from single-unit test turbine measurements to predict variability across large turbine populations.

The ideal candidate is motivated by complex, interdisciplinary challenges and has a strong foundation in data science, electronics, or systems engineering, with a willingness to learn across domains. Professional qualifications include:

• MSc in Computer Science, Electrical/Electronics Engineering, Data Science, Cyber-Physical Systems, or a closely related field.
• Experience with machine learning algorithms, especially for time-series data, anomaly detection, or edge computing (TinyML).
• Strong understanding of IoT communication protocols, data resilience, and cybersecurity principles.
• Familiarity with signal processing for high-frequency sensor data (acoustics or vibration) is advantageous.
• Proficiency in Python for data science and ML prototyping; experience with C/C++ or embedded programming for edge devices is desirable.
• Statistical intuition for working with sparse data and low-probability events.
• Collaborative mindset, strong communication skills, and self-driven research ability.

PhD stipends are allocated to individuals holding a Master's degree and are normally for a period of 3 years. Enrollment as a PhD student at the Technical Doctoral School of IT and Design is required, in accordance with Danish Ministerial regulations. Salary and employment terms follow the AC collective agreement, providing a competitive stipend and benefits.

The research group focuses on networking and edge/cloud computing solutions, primarily in the context of 5G and beyond, with applications in automation, augmented/virtual reality, Industry 4.0, healthcare, and smart homes. More information about the group can be found at https://ecn-aau.github.io/.

To apply, submit your application, CV, diplomas, and other relevant documents via Aalborg University's recruitment system. The application portal is accessible through the job advertisement link. The university values diversity and encourages applicants from all backgrounds. For questions, contact Associate Professor Sokol Kosta or Lisbeth Diinhoff.

Application deadline: August 1st, 2026.