PhD position on AI-driven Multiscale System Modelling for IoE Digital Twin

This PhD position focuses on advanced research in AI-driven multiscale system modeling specifically applied to Internet of Everything (IoE) digital twins. Candidates should have a strong foundation in artificial intelligence, including machine learning techniques and data-driven modeling approaches. Expertise in multiscale system modeling is essential, encompassing the ability to integrate and simulate complex systems across different spatial and temporal scales. Familiarity with digital twin technology, particularly within the context of IoE, is important, including knowledge of sensor data integration, real-time system monitoring, and virtual representation of physical assets. The role requires proficiency in relevant programming languages such as Python, MATLAB, or similar tools used for simulation and AI development. Experience with system modeling frameworks and simulation environments will be advantageous. Candidates are expected to have a robust analytical skill set, with the ability to design and validate models that accurately reflect real-world system behaviors. Strong problem-solving capabilities and a research-oriented mindset are critical for contributing to cutting-edge developments in this interdisciplinary field. While no specific experience level or education points are provided, the position demands a high level of technical competence and academic rigor consistent with doctoral research standards in computer science, engineering, or related fields.