Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- The University of Manchester
- Linköping University
- NTNU - Norwegian University of Science and Technology
- Nature Careers
- University of Luxembourg
- University of Oslo
- University of Tübingen
- BRGM
- Delft University of Technology
- Forschungszentrum Jülich
- Fritz Haber Institute of the Max Planck Society, Berlin
- INRIA
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Max Planck Institute for Mathematics in the Sciences
- NTNU Norwegian University of Science and Technology
- Newcastle University
- Queensland University of Technology
- Swansea University
- Umeå University
- Umeå universitet
- Universite de Montpellier
- University of Adelaide
- University of Antwerp
- University of Birmingham
- University of Bonn •
- University of Cambridge;
- University of Twente
- University of Twente (UT)
- 19 more »
- « less
-
Field
-
reservoir engineering, the main research is focused on mathematical physics, exact and asymptotic solutions of non-linear partial differential equations, and analytical methods in fluid mechanics. MSc
-
. Liu, Fourier Neural Operator for Parametric Partial Differential Equations, arXiv:2010.08895, 2020. [10] B. Shahriari, K. Swersky, Z. Wang, R. P. Adams and N. de Freitas, Taking the Human Out
-
discipline. Programming skills in any language and knowledge of numerical methods for solving differential equations are highly desirable. Knowledge of heat transfer is advantageous. Applicants are expected
-
Hamiltonian systems, Floer homology, analysis and applications of Dirac operators, symmetries of differential equations, geometric mechanics, Finsler geometry, …. You will organise your own PhD research and
-
, groundwater flow simulation, and numerical model development Basic knowledge of numerical methods for solving nonlinear systems of partial differential equations (e.g., finite volume method, finite element
-
nutrients with the soil through adaptive root and fungal networks. The successful candidate will design and implement a modelling framework based on Partial Differential Equations (PDEs) to represent
-
of numerical methods for solving nonlinear systems of partial differential equations (e.g., finite volume method, finite element method) Experience with open-source CFD software such as OpenFOAM, PFLOTRAN
-
probabilistic modelling Familiarity with stochastic processes (e.g., Markov chains, stochastic differential equations) Prior exposure with Transformer architectures or large-scale sequence modelling Prior
-
based on Partial Differential Equations (PDEs) to represent the coupled dynamics of roots, mycorrhizal fungi and soil resources under varying environmental conditions. The work will integrate concepts
-
work assignments A wide variety of physical phenomena like radio transmission, ultrasound, acoustics, or tsunami modelling involve the solution of partial differential equations (PDEs) that model wave