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Range: $81,293 - $109,307 per annum (plus 17% superannuation) We are seeking a Research Fellow with experience in machine learning research and development, particularly with a specialisation in such
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focused on securing systems and addressing data privacy and security challenges in machine learning. About You To be successful for this position, you will have: Demonstrated ability to prepare and deliver
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time-management skills with exceptional attention to detail Confidence working both independently and as part of a team Excellent communication and interpersonal skills Sound computer literacy and
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of the university’s largest schools, with a rapidly expanding teaching and research portfolio. The School is at the forefront of emerging fields, including Artificial Intelligence, Machine Learning, Quantum
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administration and communications Proficient computer skills (MS Office) and related technology A detail-oriented and a growth mindset Well-developed planning, organizational and problem-solving skills
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this project, we will develop automated approach to detect the defects in AI systems, including LLMs, auto-driving systems, etc. Required knowledge - self-motivated, willing to spend time and efforts in research
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Rugged, field-proven connectivity solutions Chimera Land OBDII Odometer Air Data Unit Poseidon Kinematica Industries Defense Military-grade navigation in GPS denied or contested environments Tactical
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Multi-modal Machine Learning—including areas like Neuro-symbolic AI, Knowledge Graphs, Contextual AI, Conversational AI, and Trustworthy & Safe AI. This role also offers the opportunity to explore human
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systems and applications including word processing, spreadsheets, presentations and demonstrated ability to learn new applications. Excellent time management skills, with a demonstrated ability to respond
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern thinking, connecting decades of computer science methodologies with modern data and