Sort by
Refine Your Search
-
Listed
-
Field
-
Candidates should hold a previous degree (Bachelor’s and/or Master’s) in Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering, with demonstrated knowledge in machine
-
research record in one or more areas of theoretical quantum science, including: Quantum computing Quantum information Quantum communication Quantum sensing Quantum optics Quantum materials Quantum energy
-
accounting software, advance level of using Microsoft Office suite of applications such as Power BI and Power query as well as Excel modelling, utilisation of web technology and experience in the use
-
Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much less advanced than for other forms of data. Our research is revolutionising the analysis of time...
-
The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon...
-
area Software Engineering The objective of this project is to design automated approach to detect bugs in various software, e.g., compilers, data libraries and so on. The project may involve LLMs
-
Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Testing AI/LLM systems Primary supervisor Yongqiang Tian Research area Software Engineering In
-
testing approaches that can be used to verify that machine learning models are not biased. Required knowledge Software engineering, software testing, statistics, machine learning
-
evaluation Applications of AI in biomedical research This project is suitable for students with an interest in genetics, computational biology, or data science. A background in statistics, computer science
-
of the University’s rich experience agenda, including the Parbinata program. This flagship initiative will transform the Clayton campus into a hub for Indigenous knowledge sharing, integrating First Nations