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Field
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will explore how semantic digital twins can automate the generation of control-oriented models and how LLMs can facilitate natural language interaction with complex building management. The developed
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the algorithm development team; to find relevant real-life benchmark tests, and to compare our developed methods against state-of-the-art. You will join a strong academic team at DTU Management’s Management
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This project develops quantum-AI tools to optimise urban hydroponic food systems and evaluate their therapeutic impact on student well-being. The expected outcome is to create quantum-reinforced AI
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Technology, Dep. ETI / Embedded Systems, we are looking for a researcher as of the 01.04.2026. Your tasks: Development of architectures and algorithms for adaptation of time-triggered systems based
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to run these algorithms, i.e., the AI data centers, are extremely power hungry, thus significantly increasing the burden on the electrical grid. More importantly, the unique AI data centres load patterns
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the Unconventional Communications and Computing Laboratory (UC2), led by Dr Michael T. Barros, which develops modelling and algorithmic methods for networked communication and computation under real-world constraints
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fabrication facilities as well as high performance computing (HPC) facilities at QUT. PhD2: Pore-network modelling of reactive transport As a PhD student, you will develop efficient pore-network modelling
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to improve our understanding of disease and the effectiveness of treatments, and implementing AI algorithms to deliver safer and more efficient care. The student will have access to a unique training programme
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plus. You enjoy working with complex, multimodal datasets and developing robust algorithms for continuous monitoring and predictive modelling. You are comfortable combining coding, data analysis, and
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will examine the suitability of NIST-standardised post-quantum cryptographic (PQC) algorithms in realistic network settings and explore hybrid approaches that combine classical and post-quantum