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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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in AI and cybersecurity to develop novel solutions to cyber-resilient AI for the benefit of Swedish industry and society. The vision is to make Sweden a role model in secure trustworthy AI by
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development related to the above areas. Publications in first class journals and highly competitive conferences in areas relevant to the work, i.e. network modelling and protocol emulation in virtualised
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data visualisation, for example work with regression models or GLM‑based analyses. Experience with research on dog behaviour and with carrying out behavioural tests is considered an asset. You must have
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biological matrices. Hands-on acquisition of SERS data from biologically and clinically relevant samples, including in vitro bacterial cultures, experimentally infected wound models, and clinical wound samples