84 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UNIS" positions at Monash University
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Authorised by: Marketing, Faculty of IT , Monash University . Maintained by: Marketing, Faculty of IT . Copyright © 2024 Monash University. ABN 12 377 614 012 Accessibility - Disclaimer and copyright - Privacy , Monash University CRICOS Provider Number: 00008C, Monash College CRICOS Provider...
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analyse and harmonise large-scale claims, service and payment data across multiple jurisdictions—delivering insights that can influence national injury prevention and health policy. You’ll be part of
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This project will seek to further the research into and development of machine learning techniques that may be used to triage, classify, and otherwise process material of a distressing nature (such
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collaborative research, further developing expertise within the field. Key Responsibilities Conduct research on complex quantum processes, particularly using the process tensor formalism, and leverage practical
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on clinical trials Well-developed planning and organisational skills, with the ability to prioritise multiple tasks and set and meet deadlines Capacity to work in a collegiate manner in a team environment and
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systems are based on the Cassowary algorithm , developed in part by Monash researchers. While constraint-based layout is powerful, it can be difficult for users to understand the interactions and behaviour
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The project involves design, implementation and evaluation of rule-based chatbot to support students when they study information from multiple texts, e.g., reading a few articles about global
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The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information
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group of experts to predict (probabilistically) whether these occupations will be automated, augmented or unaffected by emerging technologies. Using this data, a classification algorithm is then trained
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, representing a significant reduction of the cost of the MRI scan per patient. This project will develop cutting edge data processing methods for mobile MRI scanners and testing in clinical enviroment.