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part of the MARTINA project and will explore the application of co-design optimized machine learning and neuromorphic solutions for applications that are challenging to address using conventional
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areas, engaging in both theoretical and experimental research in: Data-driven and learning based control - Data-driven adaptive motion planning - Cognitive reasoning, symbolic knowledge representation
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into two main areas: (1) material development and characterization to ensure optimal sensing and mechanical performance, and (2) structural evaluation of SS-FRCMs under environmental stressors such as freeze
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higher availability. Through well planned maintenance, external and internal operational risks can also be controlled and minimized. The subject area/division of Operation and Maintenance Engineering is
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-quality infrastructure such as laboratory facilities for rocket propulsion, small satellites, asteroid engineering, and space avionics. Subject description Space systems includes systems for control
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tools and procedures for cloud-to-edge compute continuum. -Dynamic Resource and Compute Management for cloud-to-edge compute continuum. -Unified Monitoring Interfaces to provide scalable control and
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risk analysis. -Testing for security and security countermeasures analysis and implementation -Access and usage control for secure data sharing in industrial eco-systems. -Virtualization at the cloud