342 computer-programmer-"https:"-"U"-"FEMTO-ST" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Monash University in Australia
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, delivery, governance and reporting. A key focus of this role is serving as Program Manager for the MRFF-funded CALIPSO trial, while also contributing to the coordination and expansion of other national and
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systems. The fast growth, practical achievements and the overall success of modern approaches to AI guarantees that machine learning AI approaches will prevail as a generic computing paradigm, and will find
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This is a rare opportunity to establish and grow a world-class research program at the heart of Monash’s growing quantum technologies ecosystem. We are especially keen to attract candidates whose work
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management, distributed computing, and energy-aware computing, preparing them for impactful roles in industry and research. Key Components and Example Scenarios Predictive Resource Allocation and Load
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this website but submit the Expression of Interest via the Monash Data Futures Institute Application Link: https://www.monash.edu/data-futures-institute/study/phd-scholarship/mobility-data-driven-planning
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into AI systems or mathematical and computational models of brain function. This project would be for someone who wishes to pursue a deeper understanding of humans and machines and the meaning this has
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research projects will be embedded in a wider research program funded by an NHMRC Ideas Grant focused on advancing adaptive platform trials by incorporating new external research as it emerges. The two PhD
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for assisting with program delivery in collaboration with student leaders and faculty representatives, project scoping and identifying deliverables; and monitoring, evaluating and reporting on program and project
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for inference, yet differs from standard Bayesian approaches through its information-theoretic foundation. The MML87 approximation achieves computational tractability while remaining virtually identical to Strict
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The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them using data extracted from software repositories. This fine-tuning process aims to enable the models...