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of this project include: Co-design and coordinate field experiments and workplan for HTFP data collection Contribute to field work and to the collection of HTFP data from various phenotyping devices such as the FIP
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team works on (i) advancing our understanding of mechanotransduction in 3D, (ii) designing hydrogel-based 3D scaffolds with tunable properties, and (iii) using these to design 3D disease models and drug
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stimulation techniques. The goal is to develop safe, efficient, and environmentally acceptable stimulation strategies for geothermal applications across Europe. Job description Plan, conduct and analyse
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study is of highest priority. The mission concept study will finalize the required satellite architecture, conduct key technical trades, and finalize the overall mission development plan and
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of hybrid AI-optimization modelling. This position focuses on the design of AI-based surrogates of large-scale energy system models and will be integrated in the activities of the Nexus-e group with close
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infrastructure Designing and running systematic evaluations of model performance, robustness, and reliability Building datasets, benchmarks, and pipelines for legal AI applications Improving model architectures
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. In this project, we aim to develop cross-modal AI models for MSK health evaluation by linking diverse clinical imaging datasets. The central innovation is the creation of a shared, tokenized latent
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through the use of novel materials and focused design to leverage their unique properties, with the knee as the example case. You will gain the necessary interdisciplinary skills demanded by industry and
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they are maintainable, transferable, and ready for operational use. Across all phases, you will co-design solutions with users and domain experts, participate in collaborative workshops, and iteratively refine
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100%, Zurich, fixed-term ETH Zurich’s Energy and Technology Policy Group (EPG) is looking for a doctoral student working on the role of knowledge and innovation for economic resilience in