We are seeking a highly motivated and skilled Postdoctoral Researcher to join our working group in the field of
Computational Fluid Mechanics. The successful candidate will contribute to an exciting three-year project focused
on inverse modelling of compressible fluid flow using high-speed Schlieren and PIV images.
The project involves developing and applying advanced numerical methods for solving the Navier-Stokes
equations, both forward and adjoint solutions, to invert experimental data from high-speed imaging techniques.
The successful candidate will be expected to work closely with our experienced team in the field of adjoint
data assimilation to develop innovative solutions, based upon an existing numerical framework.
Responsibilities:
* Develop and implement advanced numerical methods for solving the Navier-Stokes equations
* Invert high-speed Schlieren and PIV images using forward and adjoint solutions
* Collaborate with our research group to develop novel inverse modelling approaches
* Publish research findings in top-tier scientific journals
Requirements:
* Ph.D. in Computational Fluid Mechanics, Mechanical Engineering, or a related field
* Strong background in numerical methods for fluid flow simulation (Navier-Stokes equations)
* Proficiency in programming languages such as Julia, Python, C++, or Fortran
* Excellent communication and collaboration skills
* (ideally:) Experience with high-speed imaging techniques (Schlieren and PIV images, AI, Physics Informed Machine Learning)
What we offer:
* A three-year, 100% TVL 14 postdoctoral position in a dynamic and experienced research group
* Opportunities for professional growth and development in a cutting-edge field
* Collaborative and stimulating working environment