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document fossil turtle specimens Process and analyze digital CT datasets of cranial and neurological structures Carry out geometric morphometric analyses to study shape variation Conduct eco-morphological
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effect on assembly and collaborate to quantify the effect on optical properties. Our goal is to self-assemble NPLs into 1D, 2D and 3D superstructures and understand how ligand shells affect the process
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any specific questions about the position, kindly contact Prof. Dr. Marco Thines at marco.thines(at)senckenberg.de For data protection information on the processing of personal data as part of
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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stochastic differential equations based on the path signature of the driving process. We are looking for: The applicant should hold a completed PhD in Mathematics or nearby field (at the starting date