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includes, but is not limited to: photonic data processing and communication systems; AI-driven optical signal processing and network optimisation; machine learning for photonic systems modelling, control
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of interactive web-based and/or immersive analytics environments that integrate temporal networks, heterogeneous spatial-temporal data, and AI-driven forecasting and simulation models. These environments will
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prompts for AI-driven tasks using modern frameworks to ensure effective agent performance and precise task execution. Collaborative Development - Work with other technical teams (e.g., Data Engineering
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) Time series modeling, forecasting, and real-time monitoring in dynamic bioeconomic systems Data-driven modeling and intelligent control in bioeconomic systems Out-of-distribution (OOD) generalization in
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approaches for identifying, modelling, and integrating uncertainty factors originating from IoE devices and system dynamics, combining data-driven learning with knowledge-based modelling techniques
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 21 days ago
conditions: Scientific area: Bachelor’s Degree in Systems Engineering. Work plan: Model-based digital twins supported by physics-informed machine learning for multiphysics modeling. 1. Grant duration and
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(SustainCARE, https://doi.org/10.3030/101220359 ), led by Dr. Yun Liu. SustainCARE brings together heritage science, building physics, advanced modelling, and climate-conscious preservation, offering a unique
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on the track of Cyber-Human Physical Systems seeks researchers to advance Systems Science and Engineering by modeling human behavior in complex dynamic networks addressing global challenges. Emphasizing Cyber
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pioneering research in process systems engineering, with a focus on first principles and data-driven modeling, simulation and optimization with strong and permanent interactions with experiments. Integrate
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the production of spatially granular and engineering driven representations of model results. Experience working across disciplines in multi-institution and multi-stakeholder collaborations is desirable