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postdoctoral researcher with: A PhD (or near completion) in Computer Science, Computational Biology, Mathematics, Bioinformatics, or a related discipline. Proven expertise in machine learning and algorithm
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commercially orientated research projects in computer vision and machine learning. To be successful you will need: A PhD in Computer Science, Engineering or other Machine Learning-related field. Programming
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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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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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record of computer programming. Experience in numerical relativity and/or numerical simulation of quantum field-detector interaction Strong written and oral communication skills. Demonstrated ability
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(Academic Level A) Visa sponsorship may be available for this position Based at our St Lucia Campus - Brisbane About This Opportunity If you are passionate about computational modelling, thrive on solving
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
materials and systems. Research Fellow – Micro/Nano Manufacturing for Electrochemical Technologies Open to PhDs in Materials Science or Chemical/Electrical Engineering with a strong background on micro
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
. This position is a fixed term appointment for a period of 2 years. Research Fellow – Electrocatalysis for Hydrogen Production Material Scientist or Chemical/Electrical Engineer - Catalysis Open to PhDs in
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, with a specific focus on complex biological systems. The project aims to apply highly controlled optical trapping techniques to investigate cell–fluid interactions during macropinocytosis (“cell drinking
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the timing, scale, and rate of mammal declines in Australia. They will use critical inferences of past demographic change and high-performance computing to disentangle the ecological mechanisms that were