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Job Record #15536
TitleMachine Learning Acceleration of CFD
CategoryPostDoc Position
EmployerThe National Energy Technology Laboratory
LocationUnited States, West Virginia, Morgantown
InternationalYes, international applications are welcome
Closure DateSunday, March 31, 2019
The ML-CFD research group at the National Energy Technology Laboratory 
(NETL) has formed a new effort centered around the acceleration of 
Computational Fluid Dynamics (CFD) using machine learning and hardware 
acceleration (GPU’s, TPU’s, FPGA’s, etc).  NETL has developed software links 
between MFiX (NETL’s inhouse CFD code) and Google’s TensorFlow.  NETL is 
using TensorFlow to shift computational load to advanced accelerator 
hardware as well as develop ML based algorithms and/or hybrid algorithms 
that can significantly increase computational speed while maintaining 
accuracy.  This is bleeding edge research that has already proven to 
dramatically reduce time to solution.

Experience with high performance computing platforms and CFD software 
packages such as the NETL MFiX Suite (most preferred), ANSYS FLUENT, CPFD-
Barracuda, or OpenFOAM is preferred.

In addition, experience with TensorFlow (most preferred) or another ML 
software is highly preferred. 

An M.S./Ph.D. degree in engineering, computational science, mathematics or a 
closely related discipline is required.

Working knowledge of Fortran and Python is strongly preferred.


Contact Information:
Please mention the CFD Jobs Database, record #15536 when responding to this ad.
NameDirk Van Essendelft
Email ApplicationNo
Record Data:
Last Modified15:37:59, Monday, December 17, 2018

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