Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- NTNU Norwegian University of Science and Technology
- AWI - Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Ariel University
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); Published yesterday
- GFZ Helmholtz Centre for Geosciences
- Instituto de Engenharia Mecânica
- KU LEUVEN
- Leibniz
- Loughborough University
- Monash University
- NTNU - Norwegian University of Science and Technology
- Nature Careers
- TU Darmstadt
- Technical University of Denmark
- Technical University of Munich
- University of Newcastle
- University of Strathclyde;
- Utrecht University
- Wageningen University & Research
- 11 more »
- « less
-
Field
-
streaming, modulating hydrodynamic drainage and confinement, and thus tuning the balance among dispersion, hydration, and electrostatic forces. By coupling rapid field actuation with force spectroscopy and
-
miscible) is approached. Moreover, as the correlation length diverges, fluctuations become increasingly important and the physics of these fluctuations has to be considered and modelled near the liquid
-
thesis, (assignment) report or other publication demonstrating your experience in numerical modelling of (complex) fluid flow problems. Specific experience in the modelling of hydrodynamics (turbulence
-
sensing (e.g., PlanetScope, Sentinel-1), advanced numerical modelling (HEC-RAS, Delft-FM), and targeted field surveys to map mining intensity, simulate channel adjustment, and assess changing flood hazards
-
analysis framework that supports flood-resilient urban design by combining multi-sensor Earth observation (EO) data, hydrological–hydrodynamic models, urban digital twins, and advanced AI methodologies
-
and simulation of PV systems and other offshore renewable energy technologies; hydrodynamic and fluid dynamic systems; programming and numerical modelling (e.g. Python, MATLAB); computational fluid
-
experimental data from hydrodynamic labs for validation purposes. Apply the AI models to develop an AI-based decision support framework for operability assessment for ships in planned voyages under forecasted
-
data from hydrodynamic labs for validation purposes. Apply the AI models to develop an AI-based decision support framework for operability assessment for ships in planned voyages under forecasted
-
to significantly reduce the turnaround time of SRS, thus enabling their use for industrial design processes. By combining state-of-the-art numerical methods and data-driven modelling techniques, the PhD candidate
-
methods and data-driven modelling techniques, the PhD candidate will investigate novel frameworks to accelerate SRS in HPC environments. The PhD candidate will work at the Ship Hydrodynamics section