Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
to buildings (either using simulations or real cases). Knowledge or previous experience with building automation is a plus. Knowledge or previous experience with database management, modeling, or engineering is
-
; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
-
://www.ntnu.edu/ept ) at the Norwegian University of Science and Technology (NTNU) is seeking a PhD candidate to work within process modeling and simulation of novel zero-emission oxy-fuel combustion CO2 capture
-
outcomes. Computational biomechanical models of the MV will be developed to offer new insights, create mechanical markers for MR progression, and evaluate repair techniques through simulations. Despite
-
guidelines for appointment as PhD, post doctor and research assistant. As a result of the new Act relating to universities and university colleges with associated regulations of 01.08.2024, NTNU has, during a
-
relevant component development tasks in the project Contribute to relevant simulation and modelling activities in the project Required selection criteria You must have a professionally relevant background in
-
, training deep learning models to adapt designs to boundary conditions, and integrating FEM workflows within parametric modeling environments like Grasshopper. The candidate will contribute to building a
-
-cycle fatigue. The research methods are based on both small-scale and full-scale experimental testing and on Finite Element Modelling. Are you motivated to take a step towards a doctorate and open
-
energy systems. The work will build upon theoretical and simulation-based models developed at NTNU and MIT. As different carbon-free energy carriers are expected to be highly connected in the future
-
, compared with state-of-the-art rule-based methods as baselines. Design of control barrier functions (CBFs) considered for safeguarding control setpoints. Dynamic programming and model-predictive control