Many technologically important material properties are closely related to disorder and short‑range structural correlations. Diffuse scattering observed in a diffraction experiment on crystalline materials contains the information on dynamic and static disorder. Relating this information to the underlying structural disorder is a challenging task, particularly in the case of single‑crystal diffraction data where the information extends towards 3‑d space. Machine learning offers promising approaches for the solution of complex disorder problems, ultimately aiming at a general and automated workflow for the analysis of single‑crystal diffuse scattering. In this project you will have the opportunity to contribute toward reaching this challenging aim.
In addition to exciting tasks and a collegial working environment, we offer you much more:
We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation/identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.
The following links provide further information on diversity and equal opportunities: and on the targeted promotion of women:
#J-18808-LjbffrVeröffentlichungsdatum:
14 Mär 2026Standort:
JülichEinsatzort:
Jülich, GermanyTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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