300 phd-studenship-in-computer-vision-and-machine-learning PhD positions in Australia
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the academic staff at SIT. We are looking for PhD students to work on projects on stochastic optimisation algorithms for hyper-parameter tuning in Machine learning. The successful candidate will explore
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We are seeking an outstanding candidate for a PhD scholarship (including an overseas student fee waiver) based at Flinders University for an ARC Discovery Project entitled: Pacific Powers: Imperial
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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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and closing dates, see: Melbourne Social Equity Institute PhD Scholarships Open Call Benefits The scholarship provides benefits as per the Research Training Program Scholarship page In addition
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interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
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AI & Cyber Futures Institute - Charles Sturt University | Bathurst, New South Wales | Australia | 9 days ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Available Scholarships PhD Student Scholarships: Development
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project management skills. Candidates with strong skillset, including familiarity with structural health monitoring, computer vision and machine learning are desired for this project. Must be eligible
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Scholarship base Merit Based Value CSIRO shall award the student an iPhD Program Scholarship annually (GST exempt), starting at $35,000 (2025 rate), indexed at 3% annually, for a maximum of 4 years. This is
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the government and organised science in Britain. To expand upon his research, which brought new information to light and many new questions to be explored, the Mark Govier PhD Scholarship will support innovative
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these constraints into the training objective, complicating model training. This project aims to leverage advancements in computer vision, particularly in implicit neural representations, to embed priors in neural