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mission standards. Core challenges: translating advanced algorithms into field deployable and operational systems managing complex technical integration across multiple consortium partners and international
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Centre for Advanced Robotics Technology Innovation (CARTIN) is looking for a candidate to join them as a Research Fellow. Key Responsibilities: Develop novel algorithms for multi-agent inverse
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recommendation mechanisms based on semantic analysis and natural language processing, with the aim of facilitating collaboration and convergence of proposals. Developing and training NLP algorithms in multiple
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in artificial intelligence (AI) for settings involving multiple interacting decision-makers---whether autonomous AI agents, humans, or a combination of both. Applications include mixed-autonomy
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from multiple disciplines and institutions. RESPONSIBILITIES: Write code and develop novel theoretical and practical state of the art artificial intelligence/machine learning algorithms that are focused
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
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 | about 2 months ago
: PD&PEWER Level A&B Postdoctoral - Research Fellow _ CSS.pdf This position will provide opportunities to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited
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use of data and algorithms. Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders, e.g., academics, business executives
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences