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) is seeking a talented academic to join as a Lecturer in Machine learning and Computer Vision. We are looking for a teaching and research academic with a strong expertise in applied AI and current
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for mining and aerospace applications. This may interest scientists/engineers in fields such as physics, mathematics, computer science with experience in computer vision. The position is based in Brisbane, co
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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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learning, artificial intelligence and computer vision. With world-leading researchers, modern facilities and an innovative culture, we're committed to delivering research that is highly valued by our local
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Application Deadline 16 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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-model fusion”. The successful candidate will develop near-real-time integration between emerging environmental and ecological AI-driven data sources (e.g., automated acoustic and machine vision species
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exceptional outcomes for students, staff, and the broader community. Balance strategic vision with rigorous program management, delivering clarity of scope, timeframes, risks, and financial outcomes. To be
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team, whose aim is to provide a high quality learn to swim program to our community. Deliver fun and engaging learn to swim classes in line with Macquarie University Learn to Swim program. Utilise
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🎯 Research Vision The next generation of software engineering tools will move beyond autocomplete and static code generation toward autonomous, agentic systems — AI developers capable of planning
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Drive innovation in traffic video analytics by building and optimising cutting-edge computer vision models that improve road safety and transport planning. Full-time appointment on a fixed term