Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Monash University
- University of Sydney
- University of New South Wales
- The University of Queensland
- University of Adelaide
- Macquarie University
- RMIT University
- Curtin University
- UNIVERSITY OF SYDNEY
- University of Tasmania
- The University of Western Australia
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- La Trobe University
- RMIT UNIVERSITY
- UNIVERSITY OF WESTERN AUSTRALIA
- James Cook University
- University of Southern Queensland
- Australian National University
- CSIRO
- Queensland University of Technology
- Charles Sturt University
- Federation University Australia
- Swinburne University of Technology
- UNIVERSITY OF ADELAIDE
- Advanced Navigation's Student Grant Program
- BOND UNIVERSITY
- Flinders University
- Murdoch University
- The University of Newcastle
- University of Melbourne
- ;
- Deakin University
- Edith Cowan University
- MONASH UNIVERSITY
- MURDOCH UNIVERSITY
- Nature Careers
- Nuclear Science and Engineering Undergraduate Scholarship - Department of Defence
- SWINBURNE UNIVERSITY OF TECHNOLOGY
- The University of Adelaide
- University of New England
- Victoria University
- WESTERN SYDNEY UNIVERSITY
- 32 more »
- « less
-
Field
- Computer Science
- Economics
- Medical Sciences
- Engineering
- Education
- Biology
- Materials Science
- Mathematics
- Business
- Environment
- Linguistics
- Psychology
- Science
- Earth Sciences
- Electrical Engineering
- Law
- Humanities
- Sports and Recreation
- Arts and Literature
- Chemistry
- Social Sciences
- Physics
- 12 more »
- « less
-
financial, personal, and confidential information. This project seeks to introduce machine learning and artificial intelligence techniques to effectively detect phishing websites. By leveraging these advanced
-
This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
-
interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
-
This research project aims to address the critical need for privacy-enhancing techniques in machine learning (ML) applications, particularly in scenarios involving sensitive or confidential data
-
. Scientific Contribution Our group has strong publication record of 100+ first or senior author top-tier (ERA ranking A*/A) journals and technical conferences in the machine learning and medical AI field. His
-
Adversarial Machine Learning (AML) is a technique to fool a machine learning model through malicious input. Due to its significance in many scenarios, including security, privacy, and health
-
With success stories ranging from speech recognition to self-driving cars, machine learning (ML) has been one of the most impactful areas of computer science. ML’s versatility stems from the wealth
-
based on matched-filter statistics. Detecting the unknown relies on the development of complex algorithms at the forefront of statistics, machine learning, and data science. This multi-disciplinary
-
Project description: Nowadays, data-driven machine learning algorithms are well suited to solve real-world problems that require high-level prediction accuracy. However, it seems as if nothing beats
-
The world is dynamic and in a constant state of flux, yet most machine learning models learn static models from a dataset that represents a single snapshot in time. My group's research is