Required background: Knowledge on enterprise architectures, systems of systems architectures, geographical information systems, self-adaptive architectures, control systems, service-oriented architectures, middleware, systems programming and model-driven engineering techniques are preferred.
Description: Design and implement a spatial enterprise control architecture for pandemic disaster management and adaptation of architectures.
Required background: Knowledge on workflow management systems, process mining, enterprise architectures, service-oriented architectures, middleware, systems programming and model-driven engineering techniques are preferred.
Description: Design and implement workflow management systems at each level of control and integrate the adopted software packages through model-based code generation.
Required background: Knowledge on data analytics, statistical analysis techniques, constraint programming, logical programming, optimization techniques, numerical methods, simulation techniques and model-driven engineering are preferred.
Description: Design and implement a high-level pandemic disaster management system, which abstracts the underlying analysis and control systems.
Required background: Knowledge on sensor networks, data analytics, machine learning algorithms and optimization techniques are preferred.
Description: This project aims to design and implement a data collection, filtering, fusion and storage, machine learning and data analytics system with a toolkit for optimizing the clusters of networks.
Required background: Knowledge on reliability, security, performance, run-time verification, optimization and model-checking methods techniques and service-oriented architectures are preferred.
Description: Enhance the enterprise architecture where needed with the help of architectural styles for reliability, security, timeliness and run-time correctness.