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models that best capture these. Asthma is a highly prevalent respiratory disease that often starts in childhood. However, asthma is heterogeneous, and several endotypes have been proposed for this chronic
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robotics Goal-driven agentic AI Autonomous medical imaging Design of AI-enhanced medical devices Machine learning models and algorithms for medical signal processing Embedded AI Privacy-aware AI Foundations
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sensor systems or mobile/web apps Document experiments, model architectures, training procedures, and results Minimum Qualifications Full Employment Eligibility Requirements can be found here: https
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functions to be developed are: Conducting in vitro and in vivo experiments with pancreatic cancer models within the parameters of the funded project. Collaboration in experimental design, as well as in data
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broad range of areas, including causal inference and time-to-event analysis, clinical trials, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling
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Kansas. The ideal candidate would have strong technical skills for working with AEM data and models, including physically based forward and inverse modeling of AEM survey responses, and demonstrated
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processes and properties using both experimental and computational techniques. The research is, as such, both fundamental and applied. Project description: The project concerns electrochemical modelling of Li
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of NeutroFLAME project is to study and characterize the unexpected function of the NADPH oxidase in neutrophils as a central break of caspase-1-dependent pyroptosis and to model the subsequent dysregulated
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About the ProjectProject details Self-adaptive and autonomous systems are increasingly deployed in dynamic and uncertain environments, where effective decision-making relies on accurate models
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accounting for Polymorphic uncertainties in Sensor Models and Sensor Fusion for IAM Operations Supervisor: Prof. Michael Kaliske, Chair of Structural Analysis and co-supervised by at least one additional