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the design of an AI test environment for open-source Large Language Models (LLMs). Research on the influence of low-frequency expert data on LLM-based systems and development of robust strategies
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with the nation-wide research priority area “LaSTing : Robust Assessment & Safe Applicability of Language Modeling: Foundations for a New Field of Language Science & Technology,” which is funded by
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climate models, archeology) to improve our understanding of these dynamics (e.g. ecosystem resilience to climate change and anthropogenic use) Derive indicators for the supply of NCPs and biodiversity from
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group Teaching and Learning with Educational Technology (Prof. Dr. Andreas Lachner) at the Institute of Education. At the heart of the project is the transformation of the re-search group into a trans
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of extension. The working language is English. The position offers a stimulating and multidisciplinary research environment, attractive remuneration under TV-L E14, and the opportunity to work at the
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: generative models for explainable patient representations, multimodal data fusion, vision-language models, and anomaly detection. Also includes student supervision and EU project coordination. Requirements
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at the intersection of computer science, computational linguistics, cognitive science, and learning technologies, and you will have opportunities to initiate or co-lead joint projects with internal and external
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Max Planck Institute for Political and Social Science, Göttingen | Gottingen, Niedersachsen | Germany | 9 days ago
partners Research experience in the Arab region and relevant language competence (Arabic, French, or both) Experience with questionnaire design, translation/adaptation, measurement equivalence, weighting
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 8 days ago
for Demographic Research, Rostock This network focuses on “scientifically motivated engineering” to design, build, and test digital prototypes—such as machine learning models and large language models—that serve as
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with