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performance should improve over time as more data becomes available. The diagnostic conclusions will be presented to an operator using a combination of AI-based fault isolation algorithms and data-driven
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. A successful candidate should have very good knowledge in quantitative methodology and related analysis tools, in particular very good knowledge in analysis with registry or survey data from various
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communication limitations, adversarial conditions, continual and adaptive learning in dynamic environments. The research will combine tools from distributed optimization, stochastic approximation, information
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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
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7 Feb 2026 Job Information Organisation/Company Linköping University Research Field Biological sciences Researcher Profile Established Researcher (R3) Application Deadline 31 Mar 2026 - 12:00 (UTC