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The goal of this project is to develop wall models for turbulent-flow simulations using deep-learning models, with a focus on deep reinforcement learning approaches. The candidate will be co-supervised by Ricardo Vinuesa and Stefan Wallin at KTH Engineering Mechanics. They will join the VinuesaLab research group (www.vinuesalab.com), engaging with projects on large-scale turbulence simulations, deep learning, and experiments. Additionally, they will have access to the multi-petaflops scale supercomputing facilities at KTH, in collaboration with the Swedish e-Science Research Centre (SeRC, www.e-science.se). The researcher will also be part of the excellent research environment FLOW (www.flow.kth.se).
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Preferred Qualifications
Emphasis will be placed on personal skills.
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Log into KTH's recruitment system to apply. Ensure your application is complete according to the instructions in the ad. Submit your application by the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time). Your application must include:
The position is offered for up to two years. A postdoctoral fellowship is a time-limited, research-focused appointment intended as a first career step after a dissertation.
KTH strives for gender equality, diversity, and equal conditions. For information about processing of personal data in the recruitment process.
According to The Protective Security Act (2018-585), the candidate must undergo and pass security vetting if the position is placed in a security class. This will be communicated during the recruitment process.
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KTH Royal Institute of Technology in Stockholm is one of Europe’s leading technical and engineering universities, known for its intellectual talent and innovation. As Sweden’s largest technical research and learning institution, we host students, researchers, and faculty from around the world. Our research and education span natural sciences, all branches of engineering, architecture, industrial management, urban planning, history, and philosophy. Read more here.
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