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systems, LLM pipelines, and evaluation infrastructure Designing and running systematic evaluations of model performance, robustness, and reliability Building datasets, benchmarks, and pipelines for legal AI
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of Environmental Engineering, ETH Zürich and matriculate in ETH Zürich. The research is related to development of experimental and modeling techniques to identify emission sources, simulate the airborne transport
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records from stalagmites which grew in coastal caves, to reconstruct the phasing of changes in the North Atlantic salinity relative to AMOC variations, and interpreting them with the aid of process models
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of velocity models using controlled test events and quality control of data acquisition Algorithm Development: Integration of multi-sensor data streams into seismological software frameworks (e.g., SeisComP
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qualitative and quantitative analytical methods to model clinician attention, verbal reasoning, and documentation behaviour Develop and evaluate machine learning models, including unimodal, fusion, and
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-project is to develop and apply advanced, patient-specific models of the knee joint fo design iteration and optimisation. Specific duties: Develop and apply a finite element model of a knee arthroplasty and
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) Separations. Job description Within a broader research program that integrates process modelling, computational materials screening and discovery, experimental synthesis, and mechanistic and performance
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facilities in Switzerland, France, Germany, UK, Japan and the USA Data analysis and modeling will be done in collaboration with research groups that specialize in theoretical and numerical calculations Profile
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dynamic biochemical processes Support in vivo tests in mouse models and clinical trials Secondments: Imperial College London (UK): Electrochemical sensing strategies University Hospital Zurich (CH): Testing
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of cardiovascular anatomy and hemodynamics. The research will integrate modern machine learning with MR signal modeling, computational imaging, and fluidmechanis, with the ultimate goal of enabling faster, more