The computational kinetics group, led by Prof. Ilya Karlin, invites applications for a postdoc position in compressible flow modelling. Our research focuses on the development of kinetic models such as the lattice Boltzmann method (LBM) or the Particles-on-Demand (PonD) method for the simulation of complex fluid flows.
This project is embedded into the newly funded ERC project PonD. PonD is a novel kinetic theory which aims at unifying computational approaches across scales, ranging from rarefied gas dynamics to incompressible turbulence and high-speed flows. Compared to classical approaches such as the LBM, stringent restrictions in terms of attainable Mach number and temperature ranges are removed, which opens a plethora of interesting flows left for us to explore in this project.
As a successful candidate, you will develop higher-order numerical schemes for PonD. This includes semi-Lagrangian or finite volume/difference realizations using high-order reconstruction approaches with variants of WENO, ENO, limiters or positivity preserving schemes. You will implement your solutions in high performance computing software and assess performance, accuracy and robustness in challenging problems for both turbulence as well as high-speed flows with shocks. The resulting scheme will then be used to conduct high-fidelity numerical simulations in extreme flow conditions as can be found in, e.g., astrophysical flows.
We look forward to receiving your online application with the following documents:
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Questions regarding the position should be directed to Dr. Dorschner (email@example.com, no applications). The review of applications will start immediately, so early submissions are encouraged.
|Title||Postdoc Position - Compressible flow modelling with PonD|
|Job location||Rämistrasse 101, 8006 Zurich|
|Published||June 15, 2021|
|Job types||Postdoc  |
|Fields||Programming Languages,   Engineering Physics,   Applied Mathematics,   Mechanical Engineering,   Computational Engineering  |