403 cloud-computing-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Monash University in Australia
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Research Training Program (RTP) Stipend Research Training Program (RTP) Scholarships, funded by the Australian Government, support both domestic and international students undertaking Research
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"A picture is worth a thousands words"... or so the saying goes. How much information can we extract from an image of an insect on a flower? What species is the insect? What species is the flower? Where was the photograph taken? And at what time of the year? What time of the day? What was the...
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their performance evaluated in terms of classification accuracy, computational speed, and overall usability. Required knowledge Deep learning (CNNs, Transformers) and computer vision Knowledge distillation for model
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computational methods for modelling social dilemmas that can account for real-world complexity in agents’ behaviour. We will build on novel computational techniques to produce realistic enough models that can be
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package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
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This project draws on a recent Dagstuhl Seminar (https://www.dagstuhl.de/en/program/calendar/semhp/?semnr=18322) that brought together leading experts from industry and academia, including those who
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potential remedial approaches - will be explored in this research program and they include (as examples): variability in staining outcomes across different stains and different sites (even within a given
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Master of Commerce Scholarship Sir John Monash Fee Scholarship The Master of Commerce is a research-oriented programme preparing students for a PhD and an academic career. Offered as part of
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Remuneration: Academic Roles: $118,974 - $141,283 pa Level B (plus 17% employer superannuation) Program Coordinator - $106,789 - $117,128 pa HEW Level 07 (plus 17% employer superannuation) Amplify your impact at
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch