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in physics-based modeling at multiple scales. We bridge the virtual to the real world by multi-parameter sensing and creating digital twins of heat-sensitive biological systems (food, humans) that can
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experience working computationally, preferably in setting up process models, and techno-economic and environmental assessments. You are interested and able to develop model-based methods for assessing costs
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their research on the spread potential and impacts of non-native plant species in mountain ecosystems based on field observations, ex situ experiments and data-driven approaches. The candidate will join a field
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Position: Bioprinting next generation functional tissues The field of tissue engineering and bioprinting is continually advancing to develop functional tissue models that more accurately mimic native tissue
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properties of bacterial communities (called “biofilms"), particularly in the context of human infections. Our projects are based on highly controlled laboratory experiments or clinical samples. Biofilms
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properties of bacterial communities (called “biofilms"), particularly in the context of human infections. Our projects are based on highly controlled laboratory experiments or clinical samples. Biofilms
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will develop and apply advanced methodologies, including scenario analysis and the innovative use of satellite data, to model the exposure and vulnerability of companies to climate-related hazards (e.g
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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with large language models (LLMs). The successful candidate will investigate both theoretical aspects – such as understanding the mechanisms and limitations of reasoning in modern LLMs – and practical
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. Empa is a research institution of the ETH Domain. At Empa’s Centre for X-ray Analytics, we investigate bio-nano assemblies from lipid nanoparticles (LNPs) to polymer-based nanosystems using powerful