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formal methods. The successful candidate will contribute to advancing data-driven modeling techniques that enable formal safety guarantees for complex dynamical systems such as autonomous vehicles
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dynamics, and how these mechanisms regulate innate immune signalling in response to microbial threats such as lipopolysaccharide (LPS). By employing genetic knockout models, advanced imaging, and metabolic
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. Applicants should have a Ph.D. in Biological/Biomedical Sciences, Microbiology, Bioengineering, or a related field, with experience in cell culture, molecular and cell biology, and animal models. Skills in
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Person Registry (Person Dimension). Will also design, develop, and validate workforce data models that integrate traditional and AI-augmented approaches. Leveraging dimensional modeling principles (Kimball
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pathways, pain perception, and tissue alterations in chronic joint disease. Using joint tissues as a biologically and clinically relevant model, the project will explore how stress-related signals interact
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in workplaces, integrating real-time data and models compliant with EN 62305-1. Where to apply Website https://careers.polito.it/ Requirements Additional Information Eligibility criteria To apply
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researchers from the modelling and experimental teams to link data and model components Your Profile: You are enrolled as a student at a German university You study Biology or a related field in natural
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? Do you like studying physical systems with wide impact in society? Then, this PhD position is ideal for you! Information This PhD project aims to develop advanced fluid models for low-temperature
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balance modelling, the research will quantify the effect of MP contamination on melt dynamics under varying conditions. Key research questions address how MPs are incorporated into snow and ice, how
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse