629 computer-science-programming-languages-"Aarhus-University" positions at Monash University in Australia
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of Machine Learning (ML) models across large-scale distributed systems. Leveraging advanced AI and distributed computing strategies, this project focuses on deploying ML models on real-world distributed
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Master of Engineering pathway program. Up to 10 scholarships valued at up to $30,000 are available each year. Applications No application required Total scholarship value Up to $30,000 Number offered Ten
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for drug discovery. Publishing peer-reviewed research and contributing to industrial software tools. About You To be successful in this role, you will have: A PhD in machine learning, computer science
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Monash University-Vietnam Government PhD Scholarship (Project 89) This joint scholarship program supports high-achieving Vietnamese candidates to undertake a PhD at Monash University. Applicants can
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experience, this is an opportunity to contribute to a national program shaping the future of dementia care across Australia. You'll work closely with a supportive and collaborative team of registry experts
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of eligibility requirements, including English-language proficiency skills, to undertake a PhD in the Faculty of Arts are available at https://arts.monash.edu/graduate-research/application-process . Applicants
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Computational drug discovery Primary supervisor Geoff Webb Research area Data Science and Artificial
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Engineering International High Achievers Scholarship Sir John Monash Fee Scholarship The Engineering International High Achievers Scholarship is introduced to recognise high achieving international
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This project focuses on brain network mechanisms underlying anaesthetic-induced loss of consciousness through the application of simultaneous EEG/MEG and neural inference and network analysis methods. In this work we study the effects putative NMDA antagonists xenon, a potent anaesthetic, and...
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computational methods for modelling social dilemmas that can account for real-world complexity in agents’ behaviour. We will build on novel computational techniques to produce realistic enough models that can be