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designs and evaluation frameworks for AI-assisted decision-making Collaborating with the technical team to study the interaction between AI systems and legal users Publishing research findings in leading
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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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(NCCR) led by PSI and UZH - as well as with the PSI's new Quantum Matter and Materi-als Discovery Center (QMMC) that will provide unprecedented opportunities for designing, making and characterizing
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for patients and clinics. We thus aim to develop a minimally invasive, injectable biomaterial platform designed to enable predictable, long-term ocular delivery of biologics while maintaining optical
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spectrum of human biology. D-HEST emphasises interdisciplinarity, translation, and technological innovation with the aim of improving quality of life. Situated in the heart of Zurich, Switzerland
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decision-making and legal reasoning in the presence of AI tools Contributing to the development of experimental designs and evaluation frameworks for AI-assisted decision-making Collaborating with
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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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of our time. Application deadline: 15 May 2026 at 12:00 midnight (CET) To apply: https://erecruit.graduateinstitute.ch/professeurs/ Please note that offers received by post will not be considered. For more
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crystallography and natural product research is required. Knowledge in enzymology, protein design, molecular biology, microbial metabolism, natural product analysis (LCMS, NMR etc.) and/or bioinformatics
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biology / X-ray crystallography, protein design, natural product analysis (LCMS, NMR etc.), microbial genetics, and/or bioinformatics are advantageous. As a doctoral researcher, you will furthermore assist