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using open-source data, assess the reliability, transparency, and applicability of these models, and validate them through applicable use-cases. Where to apply Website https://www.academictransfer.com/en
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- data assimilation towards experimental measurements under consideration of uncertainties - utilization of Explainable AI techniques to enable novel scientific discoveries - implementation of your machine
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on microscopy or time-lapse data Experience in at least one of: tracking / time-series analysis, probabilistic modelling / uncertainty, real-time or streaming pipelines Strong mathematical / statistical
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. Ideally, the model should indicate that it is uncertain because it has not encountered this situation before. This is why models must be aware of their own uncertainty: they must be able to signal when
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, ground-truth datasets, including methods for calibration, triangulation, and uncertainty quantification. Design and implement a robust translation layer that generalizes these 3D posture models to large
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ways of combining AI models from different hospitals (instead of just calculating the average model), as well as learning and propagating uncertainty in a federation. While the developed methods will be
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; and build constructive and effective relationships within team and across the organization. * Ability to comfortably handle risk and uncertainty; can act without having total picture available
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to visit the ESA website: http://www.esa.int and websites of the main conferences (co-)organised by the GNC, AOCS & Pointing Division: ESA GNC Conference, ICATT and ADCSS. Field(s) of activity
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-resolution, reliable characterization of conditioned waste drums, reducing uncertainties and supporting safe, compliant disposal in Belgium’s near-surface repository. Where to apply Website https
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–outflow measurements, providing limited insight into what happens inside the systems and leading to substantial uncertainty in design, modelling, and long-term performance predictions. This PhD project aims