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security, and prevention of adversarial attacks. Data Science: Strong understanding of data structures, algorithms, statistical analysis, and data visualization techniques relevant to AI applications. KEY
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ensuring consistency in structure, use and reportability. This includes leading campus departments in such goals. Lead system testing, validation, and deployment for Workday releases, patches, and new
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active intervention to research participation Collaborate and coordinate with intervention team and broader MIDB care team Assist with the administration of participant assessments (e.g., semi-structured
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-scale 2D video datasets, enabling reliable inference across diverse recording conditions, camera configurations, and experimental paradigms. Evaluate model performance across datasets and conditions, and
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in modeling and analysis of cyber-physical systems At the Technical Faculty of IT and Design, Department of Computer Science, a full-time postdoc position in modeling and analysis of cyber-physical
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Digital. The research focuses on advanced signal analysis and machine learning methods that enable robust operation and service continuity in future wireless networks under challenging radio conditions. As
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, plate structures, semantic data models, finite element analysis, and plugin development. The PhD position (full-time) will span 4 years of research and is funded according to standard SNSF regulations
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-party systems to ensure reliable data flow and system alignment. Consistently work to improve the integration and mapping of data between the ERP (Ellucian Banner) and the Slate CRM system. Create and
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material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property linkages based on numerical simulations and to transform them into AI
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mathematics, data science or a related discipline, together with solid skills in programming and quantitative modelling. An interest in risk analysis, structural reliability or digital twin technologies is