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Field
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applications for monitoring and managing aquatic environments under study, the Mekong river delta and the Forth river system Develop, test and apply algorithms for the processing and analysis of satellite data
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the following tasks: Development of new large language models for process modeling Development of new decision-making algorithms Provide regular project updates to principal investigator and funding agency Report
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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the COVID-19 vaccines) is a highly dynamic and fast moving field. We have developed a generative AI algorithm to optimize the mRNA, and we are looking for an experienced wetlab researcher to test the
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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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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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark
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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
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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