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Reliable and Efficient Adaptation of Large Language Models School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Cass Zhixue Zhao, Prof Nikos Aletras Application
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
to their field of expertise, contribute to the supervision of Honours and PhD students, work collegially with members of the ANU community, undertake suitable service tasks, and engage in impact and engagement
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-dominated grids, protection systems, and wide-area dynamics. Scalable algorithms and numerical methods for large-scale simulation. Scientific software and software architectures for next-generation simulation
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the content of the science they study. You will be an active member of RCNP. You will collaborate with the other postdoctoral researchers, PhD candidates and senior investigators, participate in seminars and
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interpretation algorithms. A primary application will be segmentation and quantitative analysis of PSMA PET imaging in prostate cancer, with additional projects spanning radiology-based AI applications across
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modeling and AI. This position will include: Developing new Generative AI algorithms for developing intelligent agents in areas such as planning, exploration, perception, physical reasoning, and memory
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, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: BS, MS or PhD
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PhD Scholarship - Energy-Efficient Decentralised Training Frameworks for Large-Scale AI Models on Geo-Distributed Infrastructure Job No.: 696617 Location: Clayton campus Employment Type: Full-time
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Qualifications · PhD or MD/PhD in neuroscience, molecular/cell biology, bioengineering, or a related field. · Demonstrated experience in extracellular vesicle exosome biology and advanced statistical analysis
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and/or Windows environments Working knowledge of modern development tools (Git, CI/CD pipelines, automated testing frameworks) Knowledge of data structures, algorithms, and performance optimization