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Machine Learning in Thermodynamics


In the course of digitalization in process industry, the applicability of Machine-Learning methods in process engineering is highly debated. In preliminary work at the LTD, the great potential of such methods for the description of properties of mixtures has been demonstrated. It is particularly interesting how fundamental thermodynamic knowledge can be reasonably included in data-driven approaches of Machine Learning. Possible applications include process simulations, among others.You will join an interdisciplinary team of process engineers, computer scientists, and mathematicians that work in an established cooperation of the LTD with the Chair for Machine Learning at TU Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics (ITWM). The project is furthermore conducted in cooperation with the University of California, Irvine.

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Last Change: November 20th 2019