Machine learning techniques to increase efficiency of geothermal energy production

Updated: 3 months ago
Location: Germany,
Job Type: FullTime
Deadline: 30 Sep 2022

Geochemical processes are of high importance to geothermal production. Often their impact is visible only after several years of operation. Moreover, a geothermal cascade usage covering multiple temperature ranges, and combining district heating, absorption cooling machines, greenhouse, etc., increases the overall geothermal efficiency but the geochemical processes can also occur over larger P/T ranges. One key challenge is the enhanced scaling potential resulting from the lower return temperatures. The target of the upcoming MALEG (Machine Learning for Enhancing Geothermal energy production) project is the design and the optimization of cascade production schemes aiming for the highest possible energy output by still preventing scalings.

The research will be focusing on the development of a machine learning tool to quantify the impact of the enhanced cooling on the fluid-mineral equilibrium and to optimize the operations economically. The tool will be based on results from widely-applied deterministic models and experimental data collected at geothermal plants in Germany, Austria and Turkey by our international project partners. Once fully implemented the MALEG-tool will work as a digital twin of the power plant, ready to assess and predict scaling formation processes for geothermal production from different geological settings.

In this context, we are searching for a highly motivated scientist with the ability to integrate into our international working group at KIT. This requests advanced English communication as well as basic German language skills. The position is aiming at the development of a machine learning tool and the set-up of deterministic geochemical models. The ideal candidate should hold a master's degree in geosciences or geophysics with sound interest in aqueous geochemistry and experience in numerical modeling.

Funding category: Autre financement public

The salary is based upon the salary frame agreement for the German public service sector (TV-L West, 75%, entry level E-13)

PHD title: Doctor in Geosciences

PHD Country: Allemagne

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