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performance while enabling more efficient and cost-effective maintenance. To advance the development of tabular foundation models for energy systems, we are seeking a highly motivated and skilled postdoctoral
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efficient and cost-effective maintenance. To advance the development of tabular foundation models for energy systems, we are seeking a highly motivated and skilled postdoctoral researcher. The project aims
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lab members, the group's organoid/tissue-engineered infection models (airway, gut) to prioritize physiologically relevant hits Co-supervise PhD students and contribute to method development, data
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provable guarantees AI-based cybersecurity: applying learning and AI-assisted techniques to network security, e.g., automata learning from security logs, validation of protocol models, and verified defensive
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London, and with a strong team of postdoctoral researchers and PhD students Generous access to frontier AI models and high-performance compute for proof-assistant workloads Funded travel for collaboration
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measurements; Modeling of indoor pollutant emissions, transport, transformation, and exposure, ranging from mechanistic or mass-balance approaches to more advanced computational models; and Related topics in
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to the mathematics of plasmas, with a focus on kinetic theory and PDEs. - Specific topics include stability, long-time behaviour, and mathematical properties of magnetised plasma models (such as magnetized
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other air pollutants, including source-resolved measurements; Modeling of indoor pollutant emissions, transport, transformation, and exposure, ranging from mechanistic or mass-balance approaches to more
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, environmental modelling and geospatial data science. The position is part of Vertical Africa (VERTICAF), an interdisciplinary research project funded by the Swiss National Science Foundation (SNSF). We
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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and