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utilization. The successful candidate will play a significant role in the EU‑funded TIMBERHAUS project (www.timberhaus.eu). Your tasks Develop machine learning models and computer vision algorithms for wood
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responsibility for our unique GPU-accelerated 3D FDTD software suite and extending its capabilities Modelling the effects of atmospheric turbulence fields Software development (3D modelling and coding in Python, C
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thinking with renewable energy community planning, developing methodological innovations that bridge quantitative modeling and qualitative approaches. Your tasks Develop and apply optimization and simulation
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-collection costs while maintaining validity for marketing and opinion research. Design, implement, and evaluate large-language-model (LLM) pipelines for synthetic data (fine-tuning, retrieval-augmented
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epithelium. We make use of state-of-the-art in vivo and in vitro organoid and microbiota models, omics techniques and bioengineering approaches to dissect cellular crosstalk in the intestinal mucosa in
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/current sources dedicated towards the research question. Measured data is thoroughly analyzed with state-of-the-art theoretical models and published fully open access. The aim of our research is to advance
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models and automation. We offer In this role, you will: Have the freedom to develop your research ideas and skills. Have the opportunity to collaborate internally with other ETH faculty as
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. The tasks will require a high degree of innovativeness, command of multi-scale asphalt and binder testing methods, as well as knowledge of the pavement design concepts. Experience in material modeling and
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the technical implementation, the candidate will contribute to the development of regulatory frameworks, business models, and social analyses that enable broader adoption of community PV. This interdisciplinary
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to work on a highly innovative project within a highly interdisciplinary environment Fixed contract (up to 2.5 years, with a potential extension based on additional funding) The salary is very competitive