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Field
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while maintaining computational efficiency through lower-fidelity simulation of non-critical regions, (ii) virtual sensing techniques for load and stress estimation from limited and optimally placed
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2 PhD Positions in Computational Modelling of Biological Membranes and Adaptive Functional Materials
1 – Molecular Simulations of Asymmetric Biological Membranes (CRC 1348) Biological membranes are intrinsically asymmetric molecular assemblies whose organization and function emerge from the interplay
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multiscale simulations and AI predict how a breathable material knows when to seal? In this PhD project, you will develop responsive MOF-peptide coatings for adaptive surface functionalization and derive
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access to advanced laboratories, simulation environments, and a multidisciplinary research setting. What are you going to do? As a PhD student, you will contribute to the development and validation
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computational simulation, supported by experimental investigations using test welds and novel material characterisation methods. This project is available from 1st October 2026. Applications are accepted until
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analysis: exploring relationships among quantum divergences and their role in statistical efficiency. Simulation and numerical validation: using small- to mid-scale quantum simulators and classical emulators
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computational simulation, supported by experimental investigations using test welds and novel material characterisation methods. This project is available from 1st October 2026. Applications are accepted until
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semiconductor discovery. As part of the IRTG OPTEXC program, you will work at the intersection of generative AI, computational chemistry, molecular simulation and materials science, developing computational
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ice, using a framework consisting of an ocean Large Eddy Simulation (LES) and a Discrete Element Model (DEM) of sea ice. Results from these simulations will be validated against a combination of in-situ
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
and application deadline Please submit a single PDF containing: A CV (max. 2 pages); A cover letter (max. 1 page) describing your motivation; A certified copy of your Master’s diploma and transcript