About this role
This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here. Video: https://youtu.be/Xt-yHCN5QS0 About the position The Norwegian Center on AI for Decisions (aiD) has vacancy for a PhD fellowship in Predictive AI-Based Maintenance and Optimization of Building Energy Management Systems . aiD is one of the new Norwegian AI research initiatives, funded by the Research Council of Norway and industry partners. It consists of 13 research partners and more than 60 partners from industry and public sector led by NTNU and SINTEF. All open positions will be cross-linked on the aiD website aid-center.no About the Position Are you passionate about artificial intelligence, digital twins, and energy management systems in buildings? We are offering a fully funded, three-year PhD position to develop a cutting-edge AI decision-support tool for predictive maintenance and optimization of building energy management systems and technologies (i.e., Heating, Ventilation and Air Conditioning - HVAC). Partnering with Statsbygg, the Norwegian Government’s Building Agency, your research will be deployed across a massive portfolio of public buildings. Moving beyond outdated calendar-based maintenance schedules, your mission is to solve a critical economic and environmental timing problem: knowing exactly when it becomes cost-optimal to intervene in degrading or overloaded systems. You will overcome the scarcity of real-world fault data by combining Simulation-Based Inference (SBI) and Building Performance Simulation (BPS). By integrating historical facility management (FDVU) records with live building sensor data, you will train AI models to recognize abnormal performance patterns, quantify quality-adjusted service life, and autonomously recommend whether a system needs maintenance, recalibration, or a capacity upgrade. Your immediate leader will be the Head of Department. About the project This position is hosted at the aiD Center , a premier research hub dedicated to advancing the role of artificial intelligence in complex decision-making processes. Hosted by the Norwegian University of Science and Technology (NTNU) and SINTEF aiD bridges technological, organizational, and human-centric gaps to foster a society where AI-driven value creation is safe and ethical. As an aiD-PhD candidate, you will collaborate closely with academic experts and industry leaders ensuring your research translates directly into portfolio-scale impact for the future of national real estate. You will be working with a multidisciplinary team of experts in building systems, artificial intelligence and decision-making. The supervision team includes: Prof. Ivan Depina – main supervisor and coordinator, probabilistic modelling, scientific machine learning Prof. Mohamed Hamdy – building performance simulation, building automation systems, and multi-objective optimization. Prof. Freja Nygaard Rasmussen – life cycle assessment Prof. Sebastien Gros – decision-making, energy use, AI and machine learning Dr. Signe Riemer-Sørensen - AI and machine learning, hybrid analyses Prof. Ahmed Kedir Mohammed – data analysis and machine learning Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within the framework described above Academic publications and popular science dissemination Participate in the aiD research network and engage with Statsbygg Contribute to research and knowledge exchange activities at the department Participate in international activities such as conferences and/or research stays abroad Contribute to supervision activities if required Be prepared for changes to your work duties after employment. Required selection criteria You must have a relevant master’s degree in civil engineering, mechanical power engineering or a related field. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale . If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker grade background, you may be considered if you can document that you are particularly suitable for a PhD education You must meet the requirements for admission to the Doctoral Programme - PhD - Faculty of Engineering Science - NTNU Good written and oral communication skills in English PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”. The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position. Preferred selection criteria Machine Learning Expertise: A robust foundation in probabilistic modeling, Bayesian inference, deep learning, and/or anomaly detection Modeling & Simulation Experience: Familiarity with Building Performance Simulation (BPS) tools, such as EnergyPlus or IDA ICE Building Automation System (BAS) and Building Energy Management (BEM) Data Integration Proficiency: Ability to work with complex, heterogeneous data streams Domain Knowledge Advantage: Familiarity with building energy systems, HVAC operations, or fault detection and diagnosis (FDD) is considered a strong asset Work Experience: Relevant work experience in operation and maintenance of buildings Communication skills: Good oral and written presentation skills in Norwegian or another Scandinavian language equivalent to level B2-C Personal characteristics