• a Masters degree in a discipline such as Building Technology, Architecture, Building Physics, Energy Engineering, Geomatics, Computer Science, Machine Learning or other related disciplines;
• Knowledge of building physics, energy systems and passive climate design for energy-efficient buildings and preferably experience with dynamic energy simulation tools such as Design Builder, TRNSYS or Energyplus;
• Experience with programming (e.g. with Python, command-line tools, and version control);
• Preferably experience with Spatial DataBase Management Systems for the efficient storage, manipulation and querying big (real-time) spatial data and W3C/OGC standards for sharing spatial data and models
• Preferably experience with Machine Learning techniques for time series analysis and prediction;
• Knowledge on Building Information Model (BIM), urban Digital Twin;
• Excellent oral and written communication skills in English proven by a minimum score of 100 in TOEFL or IELTS of 7.0 per sub-skill (writing, reading, listening, speaking). For more information, see https://www.tudelft.nl/onderwijs/opleidingen/phd/admission
• You enjoy performing research. You areself-motivated,self-motivated and eager to learn;
You are keen on working with partners to link real-world challenges to fundamental research questions.