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for the aforementioned reactions. Based on the automatic reactor, an I-TR-NUS&TR-L running benchtop spectrometer, and machine learning algorithms, we will be able to achieve a higher yield and control the reaction to stop
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integrated with optimization algorithms to support faster, more robust, and more adaptive decision making. The project addresses research questions like: How can learning-based models be integrated with
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absorption assessment via FDTD using EM field data Detection and localization algorithms of dynamic users using wireless signal parameters and sensor fusion Generation of Digital Twin city model that is able
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for non-terrestrial communication o Model LEO satellite and UAV communication and exposure AI based algorithms to optimize the performance of integrated terrestrial and non-terrestrial networks (coverage
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different incentives, mechanisms and regulatory scenarios, evaluating their performance with respect to different objectives and their trade-offs. Developing decentralized and bi-level algorithms to help
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that amplify human potential. The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems
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in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems tailored to dynamic, human-centered environments. They may
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; • popularisation of the results and other forms of dissemination. Competition rules Announcement reference number SOB/D110/2026/02/50-0305581 Keywords Informatics, Mathematical logic, Algorithms, Combinatorial
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logic, Algorithms, Combinatorial analysis Deadline for submitting applications: 21 August 2026 Method of submitting an application to apply for the position, candidate should send an email entitled