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depth. PhD degree in Physics, optical engineering, biomedical engineering, electrical engineering, or closely related fields Excellent skills in development of complex optical systems Experience in
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iterative validation. The project combines the generalization capabilities of large language models with symbolic constraints and formal verification backends to ensure generated properties are auditable
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courses at the Department of History; communicate the results of your research to a broader audience (through blogs, podcasts, social media etc). You must hold a PhD (or equivalent) in History. You should
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system. OCT is responsible for providing real-time visual feedback of the ablation site and controlling the crater depth. PhD degree in Physics, optical engineering, biomedical engineering, electrical
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 2 months ago
of the research initiative. In addition, you will have opportunities to develop e large collaborative projects with forest network partners, including members of the ForestPlots network. You hold a PhD in forest
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-focused , contributing primarily to one of the following projects: Project A – Synthetic Data for Theory-Driven Behavioral Research This project investigates how large language models (LLMs) produce
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: Project A – Synthetic Data for Theory-Driven Behavioral Research This project investigates how large language models (LLMs) produce synthetic responses to psychological experiments and how these compare
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. Design and implement experimental validation of metabolome-based predictions. Support and preparation of scientific reports and journal articles. Essential: PhD in (Bio)Physics, (Bio)engineering
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relationships and provide mechanistic insights. Present results at conferences, prepare reports, and publish in peer-reviewed journals. Profile You have a PhD degree in environmental, polymer, organic, colloid
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of the following projects: Project A – Synthetic Data for Theory-Driven Behavioral Research This project investigates how large language models (LLMs) produce synthetic responses to psychological experiments and how