80 machine-learning uni jobs at Monash University

Enhancing Privacy Preservation in Machine Learning

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

Measures of Simplicity in Optimisation-based Machine Learning

as a consequence of other desiderata. In the context of machine learning, many approaches propose to learn simple models since judicious simplicity can lead to good predictions [3,1]. These approaches

Machine learning based kinetic modeling on the thermal decomposition of plastic waste via pyrolysis

Computer Science and/or Chemical Engineering or equivalent; 2) Excellent mathematical and programming skills, in particular in the areas of Artificial Intelligence (AI) and machine learning including deep learning

Medical AI Exploration with Machine Learning and Robotics

. 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 for Structured Data

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

Life prediction using machine learning

, sociological, economic and web data this project will apply machine learning to build a recommendation engine that can provide life advice and predictions to individuals based on their current life situation and

Privacy-Preserving Machine Learning

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

Machine learning analysis of gravitational waves

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

Human-in-loop machine learning

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

Unlocking time: machine learning for understanding dynamic processes

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