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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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environments where terrain can change abruptly. However, formally certifying these opaque learning-based components demands impractical resources, presenting critical safety assurance challenges and delaying
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motivation for the subject Analyze data, assess different perspectives and draw well-founded conclusions Be flexible and open to adjusting the plan for the project as needed Collaborate and communicate
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catalysis. Computational chemistry allows the design and discovery of new molecules and theoretical understanding. This is especially important when studying the behaviour of sensitive chemicals, like
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programmable biomineral composites. You will perform research tasks in Work Package 2: Material Formulation, Bio-Fabrication & Characterization. Your task will focus on designing porous mineral scaffolds and
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: Artificial intelligence and machine learning. Human-computer interaction, behavioural research or experimental design. Computer vision, audio analysis or multimodal data analysis. Statistics, psychometrics
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want to develop machine learning approaches that not only withstand adverse conditions but actively learn from their own failures – and can you back those systems with rigorous formal guarantees? We
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years). The preferred starting date is the end of 2026. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings
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countries (HIC). The airm of this PhD project is to understand how E. coli colonization contributes tot he risk of diarrheal disease and infections with AMR and use this knowledge to design interventions
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of artificial intelligence and consumer behavior. • Designing, developing, and evaluating artificial intelligence (AI)-based techniques and algorithms related to consumer behavior and manipulative online