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. Its overarching goal is to rejuvenate antibiotic discovery by developing laboratory models that closely replicate in-patient conditions and using these models to identify novel antibiotics and
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. This postdoctoral position will develop and apply new experimental and modelling methodologies for the dynamic analysis of composites, suitable for liquid hydrogen fuel tanks in next generation sustainable aviation
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computational models with the "exact" but lower resolution information available from experiments. Job description: Application of specially developed approaches to define for transferable force-fields with
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-based interfaces that enable secure and intuitive interaction with AI models. Prototype and test AI tools for data summarization, Q&A, semantic search, text generation, and other advanced capabilities
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analytics, data scientists, IT, informatics, and business stakeholders to ensure AI systems are scalable, secure, and seamlessly integrated into existing workflows. This position may be eligible
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for computational design and analytical methods towards a more sustainable built environment. Information about the division/the project The Research Area Sustainable Built Environments has extensive experience in
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risk & safety, and navigation & positioning. We welcome applications from outstanding candidates working in established areas of transport such as: engineering, operations, modelling, design, flow
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primary cultured hepatocytes. These in vitro data will be subsequently used to inform mechanistic physiologically-based pharmacokinetic and pharmacodynamic (PBPK-PD) models, enabling bottom-up predictions
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the collection of empirical data through field trials and the development of prediction models based on these data. Together with the PI, the candidate is to lead the planning and execution of the project
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the lens of information processing by signal receivers. This PhD project will test fundamental predictions for the role of processing biases in shaping organism visual signal evolution and human aesthetic