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to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 15 days ago
Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning to climate, health, and environmental challenges. Strong candidates will have experience in ML algorithms, human
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opportunity, please contact Prof Michael Yu - c.yu@uq.edu.au . For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au , stating the job reference number (below) in
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, please contact A/Prof Alain Wuethrich via email to a.wuethrich@uq.edu.au . For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au , stating the job reference number
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frameworks (MOFs), and related materials using hybrid classical-quantum algorithms. A key component of the role involves using first-principles methods that capture strong electronic correlations, such as DFT
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for this appointment. Questions? For more information about this opportunity, please contact Prof Andrew Whittaker a.whittaker@uq.edu.au For application inquiries, please reach out to the Talent Acquisition team
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Lucey, and AIML Chief Scientist, Prof Anton van den Hengel, their research team, and CommBank representatives to publish high-impact research and develop innovative AI solutions for the financial sector
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. For further information about this position, please see the Position Description hyperlinked below or contact Prof. Zahir Tari via email zahir.tari@rmit.edu.au Position Description - Research Fellow, AI Please
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- Location: Wallumattagal Campus, North Ryde About the Role This position is part of the John Templeton Foundation’s project Cognition All the Way Up. The appointee will work with Dr Bourrat (Philosophy), Prof
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environment at the Department of Physics and Astronomy/ the Research Centre for Astronomy, Astrophysics and Astrophotonics. The successful candidate will collaborate closely with Prof. Daniel Terno and Prof