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Field
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to develop image processing pipelines and models for the automated evaluation of 3D data sets towards answering clinical research questions. The project is highly interdisciplinary and is carried out in close
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with the supervisor, with potential avenues including generative models, optimization tasks, or other specific applications. The candidate will work in the context of the project ML-QSIM, a 4-year, 2M
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multidisciplinary approach spans from the level of whole organisms to that of single cells, using state-of-the-art mouse genetics, multicolor “Rainbow” and Tetrachimera models, advanced imaging, flow cytometry, and
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models). Expert use of a chemical synthesis laboratory, a wide range of physicochemical and material characterisation is required. Moreover, in vitro and in vivo expertise, will be essential to determine
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learning, in particular large language models and agentic framewoks will be considered a strong asset Language Skills: Fluent written and verbal communication skills in English are required We offer A modern
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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research questions. “GenAI4Earth” will go beyond the state-of-the-art by designing, deploying, and operating trustworthy, reusable GenAI services within the EOSC ecosystem, built on FAIR data, models, and
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molecular and cell biology, transcriptomics, epigenomics and metabolomics, bioinformatics, immune fluorescence imaging, electrophysiology, and animal models of immunity in health and disease. The lab's
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and physical modelling. The goal of this position is to develop data-driven approaches to AI-based analysis of complex interaction systems and suitable hybrid architectures for this purpose
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on the candidate’s profile and interests, the position may also involve primary data collection, including extraction of medical chart data using natural language models and surveys of stakeholders within child and