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Field
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motivated and talented doctoral candidate to work on the biophysics of host-pathogen interactions using in vitro model systems mimicking chronic diseases. The project foresees ample collaborative
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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will be trained in a variety of powerful, modern analytical techniques including chemical proteomics and metabolomics. They will have access to advanced synthesis facilities, as well as biological models
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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developing and using dedicated tools and processors Contribute to our sparse auto-differentiation libraries to accelerate the training of state-space models Collaborate closely with our internal partners
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species and vegetation ecology), advanced statistical modelling using R software, and conducting fieldwork under harsh environmental conditions. A successful applicant should have good skills in English and
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy
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powerful, modern analytical techniques including chemical proteomics and metabolomics. They will have access to advanced synthesis facilities, as well as biological models, such as macrophages and organoids
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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decentralized (building-integrated) scenarios based on technical and economic criteria. Work in the EU Horizon Europe funded TREASURE project (www.treasure-project.eu) focusing on simulation models and the