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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
appointment for a period of two years (24 months) to contribute to research in artificial intelligence, with a particular focus on large language models and their applications. Applications are particularly
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focus on foundation models, medical image analysis, and multimodal healthcare data integration. In this role, you will: Develop novel federated AI methodologies, foundation model adaptation techniques
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the Acute Brain Injury leadership team, you’ll contribute to data curation, protocol development, predictive modelling, and novel analytics for large-scale neurocritical care datasets and manuscript
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innovative experimental and modeling techniques that bridge the gap between laboratory-scale physics and field-scale implementation. Our mission centers on developing next-generation solutions for energy
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projects include detecting API misuse, analyzing program performance, measuring energy consumption, detecting security vulnerabilities, supporting library migrations, and leveraging large language models
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. For more background information on the DELTA Signature Course model, as well as specific details regarding the program timeline, visit our website . Funding and Support Course launch funds: $25,000 Stipend
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Generate 3D models of human skin Train undergraduate and graduate students and other relevant lab members in techniques and the scientific method Prepare data reports for weekly meeting with PI and bi
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packages, where data, technologies and biological models will be shared across projects through joint supervision, network activities and academic and industrial secondments. The position is allocated
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, or as soon as possible thereafter. Salary will be grade 7. The main focus of this role will be on the design, collection, and analysis of novel model-based behavioural, and neuroimaging (fMRI/MEG
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of generating, from SQL queries, eBPF code executable in the kernel.; 2. Query planner optimization: definition of a cost model that estimates the execution cost of each operation in kernel space