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PhD Position: Learning thermodynamic properties ... (No replies)
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We invite applications for a joint PhD position within the MaxNet consortium for Big-Data Driven Materials Science, between the Max Planck Institutes for Polymer Research (Mainz) and Informatics (Saarbrücken), and the Fritz Haber Institute (Berlin).
The project, which runs in the departments of Profs. Kurt Kremer, Gerhard Weikum, and Matthias Scheffler, aims at applying advanced statistical methods to detect patterns and correlations in thermodynamic properties of soft-matter materials. High-throughput multiscale computer simulations enable the generation of large databases of thermodynamic properties (Dr. Tristan Bereau, Mainz), which will be analyzed to discover descriptors that link chemical structure to materials properties using both local modeling via subgroup discovery (Dr. Jilles Vreeken, Saarbrücken) as well as more global approaches, such as compressed sensing (Dr. Luca Ghiringhelli, Berlin).
Close collaborations among these groups and with other members of the MaxNet consortium will help advance the learning of thermodynamic properties in soft-matter materials. The successful candidate will be primarily located in Mainz, but extended stays at the other locations will be arranged. For more information about the groups involved, see
DESIRED SKILLS AND EXPERIENCE
Applicants should hold a Masters degree in computer science, statistics, physics, chemistry, or related discipline. Experience in a number of the following fields is mandatory: data mining and machine learning, advanced statistical methods, computational physics, thermodynamics. Strong programming skills are a plus.
APPLICATION
Interested applicants may inquire more information to Tristan Bereau or apply directly by sending a CV and contact information of two professional references to [email protected].