Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
modelling? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, both in
-
into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
-
into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
-
innovative approaches in bit technology, hydraulic hammer systems, drilling fluids, and thermal management. The project will combine experimental insights, physical modeling, digital‑twin technologies, and AI
-
Engineering at NTNU, where computational mechanics, advanced finite element modelling, and artificial intelligence meet. As a PhD candidate, you will work at the forefront of nonlinear simulation, contributing
-
experimental insights, physical modeling, digital‑twin technologies, and AI/ML methods to improve drillability, increase rate of penetration (ROP), reduce non‑productive time, and enable cost‑effective
-
. The candidate will study architectural models, including the placement and roles of quantum repeaters, memories, and control-plane functions, and how these integrate with classical networking and orchestration
-
6th April 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in magnetohydrodynamic modeling of electric arcs in silicon
-
at a pilot facility. The candidate will develop a simplified, control-oriented dynamic process model. This model will be used to propose control structures and analyze them. An available complex steady
-
operation in hybrid quantum–classical networks across intra- and inter-domain settings. The candidate will study architectural models, including the placement and roles of quantum repeaters, memories, and