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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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, Biochemistry, Biomedical Engineering, Materials Science, or Life Sciences at large. Strong interest in regulatory pathways & strategy paired with scientific curiosity and motivation to understand implantable
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formulating constitutive and damage laws that capture cavitation-driven processes, implementing and verifying robust large deformation solvers, and performing rigorous verification and validation using datasets
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Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
3 Nov 2025 Job Information Organisation/Company Academic Europe Research Field Engineering » Electrical engineering Technology » Other Computer science » Other Mathematics » Applied mathematics
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financial economics. Importantly, you have advanced programming skills to effectively manage and analyze big data. Having attended courses in Econometrics is an asset. We offer you You will be part of a
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analyzing large prospective data sets from observational and intervention studies. You have proven leadership experience in an academic environment. Your strong technical knowledge, leadership and
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applications for LISA data. Planning and deploying HPC infrastructure for large-scale gravitational-wave data analysis for LISA. Supporting additional ETH Zurich | Space projects where software engineering and
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intelligence and decision support for large fleets of civil infrastructure assets, including bridges, railways, and wind turbines. Project background The scientific aim of DIAMOND is to develop decentralized
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information across scales. In this project, you will leverage the large soil database (>2000 profiles) hosted by the Soil Functions and Dynamics group, along with soil spatial modeling techniques, to assess
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big data and machine learning methods Administrative details of Hilfsasssitent:in positions can be found here . Profile Student of ETHZ or UZH Demontrated competence in statistics, ideally including