Postdoctoral Researcher in Deep Learning for Wall Models
3 weeks ago
We are seeking a highly motivated postdoctoral researcher to join our team at KTH Royal Institute of Technology. The successful candidate will work on developing wall models for turbulent-flow simulations using deep-learning models, with a focus on deep reinforcement learning approaches.
The researcher will be co-supervised by Ricardo Vinuesa and Stefan Wallin, and will become part of the VinuesaLab research group. This provides an excellent opportunity to interact with related projects dealing with large-scale turbulence simulations, deep learning, and experiments.
The position offers access to multi-petaflops scale supercomputing facilities at KTH, as well as the Swedish e-Science Research Centre (SeRC). The researcher will also become part of the excellent research environment FLOW.
What We Offer- A position at a leading technical university with a strong focus on innovation and research
- Collaborative and dynamic working environment with engaged colleagues
- Opportunities for professional growth and development
- Access to state-of-the-art research facilities and resources
To be eligible for this position, you should have a doctoral degree or equivalent foreign degree, and be proficient in English. Relevant published work in the field of fluid mechanics is also required.
Preferred qualifications include a doctoral degree obtained within the last three years, a background in Mechanical/Aerospace Engineering or Computer Science, and international experience.
How to ApplyPlease log into KTH's recruitment system to apply for this position. Your complete application should include a statement of professional interest, CV, transcripts, contact information for references, and PhD thesis and selected scientific papers.
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