Sort by
Refine Your Search
-
characteristics To complete a doctoral degree (PhD), the candidate is expected to: demonstrate strong motivation, curiosity, and a learning-oriented mindset work independently, take initiative, and maintain good
-
are applied in real-world settings characterized by large-scale networks, stochastic demand, operational disruptions, and complex constraints. A central research question is how machine learning can be
-
principles for BGC expression and to support iterative AI-guided design–build–test–learn cycles. The precise scope of the doctoral project will be refined according to the candidate’s qualifications, the BGCs
-
collaborative learning processes Developing the research competence required to complete a doctoral degree Required selection criteria You must have a professionally relevant educational background in psychology
-
conditions, changes appear years before clinical diagnosis. Can we learn to extract them reliably? We are looking for a PhD candidate to join the Acoustics group at the Department of Electronic Systems, NTNU
-
European city with a rich cultural scene. Trondheim is the tech capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality
-
skills in English. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Willingness to learn new fields and adapt to a multidisciplinary research environment
-
): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer the opportunity to work in a very
-
. The supervision team includes: Prof. Ivan Depina – main supervisor and coordinator, probabilistic modelling, scientific machine learning Prof. Mohamed Hamdy – building performance simulation, building automation
-
-NorthWind webpage for more details): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer