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PhD Scholarship in Generative Artificial Intelligence Job No.: 686325 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment Remuneration: The successful
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discover them The Opportunity We are seeking a talented and motivated Research Fellow to join the Department of Data Science and Artificial Intelligence (DSAI) and contribute to Professor Geoff Webb’s
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Mathematics, Data Science, Computer Science Engineering, Artificial Intelligence, and Information Technology will also be considered, but it will further be required that they also have a strong interest in
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. The Lecturer may be responsible for course coordination. To be successful in this position, you’ll have as a minimum: Expertise in Information Systems, Artificial intelligence, Business Analytics, Generative AI
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advanced computational and genomic approaches. The successful candidate will work as part of a funded research project that integrates metagenomics, k-mer–based methods, and artificial intelligence
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evidence-based care, advance post-ICU recovery science, and improve long-term patient outcomes. Your expertise in analytics, artificial intelligence, and data management will directly inform how critical
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. Adaptive Prior-Dependent Correction Enhanced Reinforcement Learning for Natural Language Generation. Proceedings of the AAAI Conference on Artificial Intelligence, 35(14), 2021 Seitzer, Maximilian, Bernhard
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disciplines: Cyber Security & Software Systems (CSSS) Data Science & Artificial Intelligence (DSAI) Interaction, Technology & Information (ITI) Our PhD students and faculty conduct work leading research in many
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, artificial intelligence, or statistical modelling techniques to digital forensics, online surveillance, or large-scale data analysis, particularly in the context of wildlife crime detection and prevention
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architecture, testing/debugging skills, and version control. Experience applying machine learning, artificial intelligence, or statistical modelling techniques to digital forensics, online surveillance, or large