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research to generate research outputs of high standard Development, fitting, simulation and parameter recovery of computational models Communicate research findings through scientific publication in peer
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for light-emitting devices. Epitaxial growth, including for materials such as nitrides, is highly sensitive to detailed and often narrowly controlled process parameters, including substrate and source
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actions working on causal AI for a changing world. The AIML at the University of Adelaide is the largest computer vision and machine learning research group in Australia with over 180 members including
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tier conferences and journals in data mining/machine learning, Artificial Intelligence in Education and Educational Data Mining, Human-Computer Interaction strong technical expertise in data mining, data
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and develop an optimal (efficient, cost effective, easy to use) technological operational method for detecting and estimating wallaby populations and dynamics. What you’ll do: Develop a technological
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Sciences, Political Sciences, Computer Sciences, or Engineering, with a strong track record (relative to opportunities) in research on disaster management, extreme contexts, and resilience including a body
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not be assessed. The video may be used as part of the assessment for the criteria of presentation and communication only. The ACSPRI Executive Committee will judge the application and the ACSPRI
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-quality research publications in econometrics or related fields. You will possess the ability to solve complex statistical problems, show advanced computer literacy with proficiency in relevant software
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to work independently and collaboratively. Advanced planning, time management, and written communication skills are essential, along with proven computer literacy and proficiency in relevant software and
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Australian National University | Canberra, Australian Capital Territory | Australia | about 17 hours ago
, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning