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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials
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Cognitive Science, Medical Informatics, or a comparable quantitative discipline Proven hands-on experience working with LLMs, foundation models, multimodal AI systems, or related machine-learning technologies
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limited time until 31st of December 2032, available immediately Key Responsibilities: Design, implement and refine automated image analysis workflows, including machine learning–based methods
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, pathology and outcome data Multi-agent and predictive AI development: Develop machine-learning components for patient-trajectory modelling, recurrence and survival prediction, and integrate them
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for Digital Humanities is one of Germany′s leading institutions in the fields of digital and computational humanities. Its key areas of focus are digital linguistics, digital heritage, and AI/machine learning