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Field
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model-based control tailored to systems like NudgeFlow. The framework decomposes the global control problem into smaller local problems for each zone or room, enabling independent optimization with local
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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this requires evidence for new institutions and business models, a mindset shift to let go of what no longer works, and novel conceptual insights. This is where you come in! The aim of this PhD is to understand
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university degree (diploma, master's degree) in transport or traffic flow or related study programs. Solid knowledge of at least one programming language, preferably Python, experience in model-based
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support each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and behavioral modeling methodologies. In the FlexMobility project we propose a holistic
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for a: PhD Candidate in Emotionally and Socially Aware Natural Language Processing (1.0fte) Project description Current Natural Language Processing (NLP) systems, and especially large language models
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researched by another PhD candidate in the project. The developed methods could be applicable across many multi-agent coordination domains, from mobiltiy, to logistics and multi-robot systems. In this work, we
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contributing to new research methods in human-AI collaboration? Then we are looking for you! We are hiring a technically strong, creative, and socially motivated PhD candidate to join the international
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interaction. This requires rethinking both what we measure and how we design models. The PhD candidate will: Create datasets and benchmarks that capture emotional cues, conversational norms, and cultural
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immune cells in cell culture and murine models of inflammation and cancer Collecting, analyzing and annotating MRI data Combining MRI and mass spectrometric imaging data in data base for quantitative MRI