Forschungsstipendien, Idealo Stipendien
Theory-Experiment-Collaboration: Predicting Process Prarameters with Machine Learning and Ab-Initio Thermodynamics >> more >>
Description: Inorganic/Organic interfaces play a crucial role for the performance of organic electronic devices, such as OLED-TVs and photovoltaic cell. Of particular interest is the interface geometry, which crucially defines the device performance. However, finding optimal process parameters for optimal geometries is a tedious efforts mostly governed by tiresome trial-and-error approaches. There is, therefore, a strong need of theoretical support. To provide this support, my group and I have recently developed a Machine Learning based algorithm that allows determining the interface structure with a higher precision, and at a lower cost, than any other existing approach.
€ 2.237,60 per month, 14x per year
Oliver Hofmann email: email@example.com
Tel: 0316 873 8964 http://www.if.tugraz.at/hofmann
Or talk to the students in office PH 02 152 (2nd floor, right by the stairs)
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