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Unlocking the potential of physics-informed neural networks in fluid dynamics

Graz
beBee Careers
Inserat online seit: Veröffentlicht vor 15 Std.
Beschreibung

We are seeking a highly motivated individual to investigate the potential of Physics-Informed Neural Networks (PINNs) in fluid dynamics. This project involves a comprehensive literature review, highlighting promising use cases for up-sampling and accelerating simulations.

Literature Review

* Research the current state of PINNs in fluid dynamics
* Analyze existing methods for up-sampling and acceleration

Case Study

* Apply PINNs to 3D fluid dynamics data using a provided dataset
* Implement a Python solution leveraging TensorFlow or PyTorch

Your Profile

* Ongoing studies in Mechanical Engineering, Data Science, Informatics, or similar fields
* Experience in Python coding
* Knowledge of Data Science and Fluid Dynamics is beneficial

About Us

We offer a unique opportunity to immerse yourself in the world of fluid dynamics and apply cutting-edge techniques to real-world problems. Our team provides guidance and support throughout the project.

Successful completion of the project results in a one-time fee. We look forward to receiving your application.

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