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objectives to be achieved: The scientific work to be developed consists of: Software Architecture and Operations (MLOps)Investigate strategies to coordinate multiple specialized language models (core LLMs
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in a connected context, investigating how accelerators can be designed, integrated, and scaled for emerging large scale and networked applications. We are interested in new ways of virtualising
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training environments but without diagnosable injury. This mission is defined in several U.S. Public Laws, most recently 118-159, the Fiscal Year 2025 National Defense Authorization Act. This research
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 21 days ago
Hub (HDRH) team to define the culture, values, and ethics of the Hub at a crucial point in its development. Applied Research: Develop your own research agenda using the HDRH and ANU HASS community as
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technologies (SLA, filament printing and pellet printing), participating in the various stages of development of these projects, from the use of advanced modeling software, the application of new materials
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), participating in the various stages of development of these projects, from the use of advanced modeling software, the application of new materials; the technical development and prototyping of products
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to build a network with scholars researching political elites around the world, including an annual workshop on the topic. A friendly and inclusive workplace allowing for a good work-life balance. Attractive
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of a PhD • Expert knowledge of statistical modelling (including both theoretical and computational aspects) and use of statistical software (e.g. R - including programming). • Excellent
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, generative AI in software engineering T2: Defining requirements, preparing data, and designing generative models for an AI-augmented failure injection tool T3: Implement a minimal working prototype of the AI
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immunotherapy with graph neural networks trained on spatial single-cell tumor microenvironment (TME) data from non-small cell lung cancer (NSCLC). Using high-dimensional datasets, you will learn bi-directional