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the closing date for applications. The applicant must have good programming skills, excellent knowledge of algorithms, numerical methods, and signal processing Mandatory experience and formal training: signal
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optimisation.” The successful candidate will be involved in developing new mathematical theory and designing and implementing optimisation algorithms relevant to quantum information. The Research Fellow will
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. Develop and enhance advanced optimization algorithms for the Energy Management System (EMS), addressing energy dispatch, storage control, load scheduling, and strategies for market participation. Architect
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systems beyond commercially available peptide based systems. A6 Knowledge of data science driven approaches to drug discovery algorithms. For appointment at Grade 8: A4 Some reputation in, and insight
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to the development of innovative and sustainable low carbon plastic waste management and recycling solutions. In this project the post holder will develop novel algorithms and methods for analysis of plastic data
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the PhD has been awarded at the latest within 5 months after the closing date for applications. The applicant must have good programming skills, excellent knowledge of algorithms, numerical methods, and
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience
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Analytics & Explainability development of algorithm and system for the project The School of Computing at the National University of Singapore (NUS) invites applications for a Postdoctoral Research Fellow
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, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using