Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
In EdgeFusionAI (EFAI): Real-Time Multi-Sensor Multi-Modal Intelligence on Edge Devices, we aim to design and develop efficient techniques for fusing heterogeneous sensory data, including vision
-
This project aims to develop a computer vision system capable of detecting and classifying domestic geographic landmarks in images and video content. By categorizing locations such as “childcare
-
ideas through implementation science and health research The Opportunity The School of Nursing and Midwifery has two exciting Research Fellow positions available to contribute to the ENGAGE Project
-
innovative and transformative data platform initiatives in the higher education sector – the Monash Lakehouse. Working closely with the Associate Director, Data Engineering Services, you will help shape
-
computer science, information technology, artificial intelligence, machine learning, software engineering, computer/electrical engineering, or a closely related discipline. This PhD project is part of a
-
in analogue formats in the first place. However, the preservation of information is often a neglected aspect of community informatics projects and of information behaviour research. This PhD project
-
them The Opportunity Join the Department of Data Science and Artificial Intelligence as a Research Fellow and play a leading role in advancing artificial intelligence research for healthcare
-
development, scientific data visualisation and browser-based machine-learning deployment. Strong Python, JavaScript/TypeScript, HTML, CSS and Git/GitHub skills, together with experience in testing and automated
-
that remain secure, privacy-preserving, explainable, and clinically reliable when exposed to adversarial attacks, prompt injection, poisoned data, privacy leakage, and unsafe autonomous AI-agent behaviour
-
background in AI/ML, data science, or signal processing Interest in music informatics, emotion modelling, or multimodal AI Ability to implement and evaluate machine learning models independently Commitment