261 molecular-modeling-or-molecular-dynamic-simulation positions at Monash University
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of mobile ringtones. Traditional machine learning methods and transformer models will be used to learn patterns from audio signals and classify ringtones into predefined categories (e.g., default ringtones
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experience; a copy of academic transcripts for all higher education qualifications and contact details of two referees (at least one academic referee). a two page proposal Enquiries: should be directed by
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, including a list of any published works, conference presentations, and relevant work experience A copy of your academic transcript(s) Expression of interest is assessed by the supervisory team and shortlisted
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models (eg auto-encoders and generative adversarial networks) and reinforcement/imitation learning algorithms for Markov Decision Processes. The application areas are different problems in text processing
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primary and secondary sources, epigraphy, palynology and palaeontology. And so too can the technologies – 3D modelling, AI, animation, game engines, AR and VR, simulation and haptics. Possible lines
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innovative approaches to enhance privacy in ML models, algorithms, and workflows, with a particular emphasis on preserving confidentiality while maintaining the utility and accuracy of the learned models
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown
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people who discover them Join Monash Arts – Where Innovation Meets Excellence! Monash Arts is one of Australia's largest and most dynamic arts faculties, excelling in humanities, performing arts, languages
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In many branches of science (e.g., Artificial Intelligence, Engineering etc.), the modelling of the problem is done through the use of functions (e.g., f(x) = y). On a very high-level, we can think
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Minimum Description Length: Theory and Applications, M.I.T. Press (MIT Press), April 2005, ISBN 0-262-07262-9. [Final camera ready copy was submitted in October 2003.] Dowe, D.L., J.J. Oliver and C.S