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Computational Materials Design

Project Description

We are seeking a Ph.D. student for the development of multiscale simulation methods to work in the recently funded excellence cluster at KIT: The Cluster of Excellence is a collaboration of Karlsruhe Institute of Technology (KIT) and Heidelberg University (Uni HD) pursues an interdisciplinary approach through conjunction of natural and engineering sciences. 3DMM2O establishes scalable digital 3D Additive Manufacturing transcending from the molecular to the macroscopic scale. The goal is the ultimate digitalization of 3D manufacturing and material processing. This approach converts digital information into functional materials, devices and systems “made to order.” 3DMM2O creates a powerful technology push and pull by treating molecular materials, technologies and applications. You will work on one the development and application of multiscale materials design methods with applications in organic materials or metal-organic frameworks in collaboration with experimental groups. Work will focus on the growth/printing of nanostructured materials and their function.

Candidates should have expertise in computational theoretical physics or chemistry, or related areas and will work on topics related to the structure and function of nanoscale printable materials. We expect the ability and desire to work in a heterogeneous interdisciplinary environment, strong research skills, and a history of innovation and accomplishment documented by a strong academic record. Prior involvement in the workflow engineering, the development of complex computational methods on HPC architectures and appropriate skills in software engineering using state-of-the-art object-oriented languages is required. Successful candidates should be able to demonstrate strong programming skills in high-level languages, such as python or C++.

Funding Notes

You will paid according to the standard government payscale of the national science foundation, which is 66% E13, roughly 1800€ per month or an equivalent stipend.


1. Müller, K., J. Helfferich, F. Zhao, R. Verma, A.B. Kanj, V. Meded, D. Bléger, W. Wenzel, and L. Heinke, Switching the Proton Conduction in Nanoporous, Crystalline Materials by Light. Advanced Materials. 30: p. 1706551(2018).
2. Friederich, P., M. Konrad, T. Strunk, and W. Wenzel, Machine learning of correlated dihedral potentials for atomistic molecular force fields. Scientific Reports. 8, 2559 (2018).
3. Friederich, P., V. Gomez, C. Sprau, V. Meded, T. Strunk, M. Jenne, A. Magri, F. Symalla, A. Colsmann, M. Ruben, and W. Wenzel, Rational In Silico Design of an Organic Semiconductor with Improved Electron Mobility. Advanced Materials. 29, 3505 (2017).
4. Moench, T., P. Friederich, F. Holzmueller, B. Rutkowski, J. Benduhn, T. Strunk, C. Koerner, K. Vandewal, A. Czyrska-Filemonowicz, W. Wenzel, and K. Leo, Influence of Meso and Nanoscale Structure on the Properties of Highly Efficient Small Molecule Solar Cells. Advanced Energy Materials, 6 , 1501280 (2015).

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