522 postdoc-in-distributed-systems-and-controls uni jobs at Monash University in Australia
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Advisory System, or data from other implantable or wearable devices. This involves consideration of both feature-based machine learning or data science approaches and neural mass parameter estimation
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Identifying vulnerabilities in real-world applications is challenging. Currently, static analysis tools are concerned with false positives; runtime detection tools are free of false positives but
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maximise efficiency. This project considers a future transport system that combines flying drones with conventional ground-level trucks. In this system, as a truck approaches a customer, a drone is launched
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experience and expertise. That’s why we champion an inclusive and respectful workplace culture where everyone is supported to succeed. Learn more about Monash . This call for Expressions of Interest seeks
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Planning is the reasoning side of acting in Artificial Intelligence. Planning automates the selection and the organisation of actions to reach desired states of the world as best as possible
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Geopolitical Security) as outlined in Impact 2030 . The scholarship is available to support students with living costs whilst studying at a Monash campus in Australia. Applications closes 31 October each year
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that is vital to their lives, such as information on their entitlements, public services, health, education or work opportunities. Timely access to information is essential to perform many economic, social
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There is an opportunity to prototype digital water play systems and examine users’ aquatic body-environment interactions to derive an understanding of digital technology’s opportunities
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technologies for presenting data and information in innovative ways, perspectives have changed over time so that evaluating the worth of visualisations (for user, for task, for context) is now considered a
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while generating text. Their performance on detecting salient features from visual data is also unclear. In this project, we develop a framework to generate faithful and salient text from mixed-modal data