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for automatic segmentation and morphometry of histological images; - Compare the predictive value of AI-driven image analysis with clinical and biomarker data; - Collaborate with international experts in medical
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. Supervisory Controller Synthesis is an engineering approach to automatically derive a supervisory controller for a given discrete-event model that is safe with respect to certain requirements. Yet, the
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using deep learning and AI-driven image analysis. You will: - Analyse pre-implantation kidney biopsies according to the Banff criteria; - Apply AI methods for automatic segmentation and morphometry
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the behavior of modules into meaningful and expected behavior are becoming increasingly important. Supervisory Controller Synthesis is an engineering approach to automatically derive a supervisory controller for
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frequently proposed as a safeguard, research suggests that human involvement does not automatically lead to better and fairer outcomes—challenges such as cognitive overload, uncalibrated (dis)trust in AI, and
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hiring, yet they often reinforce societal biases, leading to unfair outcomes. While human oversight is frequently proposed as a safeguard, research suggests that human involvement does not automatically
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spectroscopy data and AI, to automatically identify textile fabrics with high accuracy in real-world sorting conditions by (1) defining optimal spectral bands, spatial resolution, and acquisition speed; (2