Scholarship funded PhD research projects

Scholarship funded PhD research projects

Do you wish to achieve excellence at a world top 100 university? Be a part of an internationally recognised faculty? If this sounds like you, please read on.

Monash IT is currently offering a number of exciting  PhD research projects with scholarship funding. We’re inviting applications from candidates willing to make a difference.

Featured research projects

Prof Mark Wallace

Optimised Routing for Personalised Public Transport

In this project a new type of personalised public transport system (PPTS) is proposed, where a fleet of autonomous or human-driven vehicles offer door-to-door and on-demand transportation. Passengers interact with the system by requesting a trip, either ad hoc or a priori, and by specifying their travel preferences. Centralised algorithms then schedule vehicles and combine trips as efficiently as possible.

Dr Marcel Boehme

Security Guarantees for Automated Software Testing

The objective of this ARC-funded PhD position is to build the first scientific framework to provide such answers with quantifiable accuracy. The candidate will explore and extend various probabilistic and statistical frameworks. Practitioners should be able to leverage a rich statistical toolset to assess residual risk, to obtain statistical guarantees, and to analyze the cost-benefit trade-off for ongoing fuzzing campaigns. As a first starting point, the perspective of software testing as species discovery (STADS) provides access to a substantial biostatistical framework in ecology to tackle this fundamental challenge. A recent vision statement provides a large number of concrete opportunities for future research.

Dr Marcel Boehme

High-Performance Fuzzing: Finding More Bugs Faster

The PhD student will work on the development of highly efficient techniques for automated vulnerability detection in large software projects. The PhD student will investigate scalable fuzzing techniques, publish in premier venues for software engineering and cyber security, and develop practical test generation tools that can detect real-world vulnerabilities in existing widely-used, security-critical C libraries. We will explore deep integrations of heavy-weight, systematic, whitebox fuzzing techniques and light-weight, random, greybox fuzzing techniques. We will also study the efficient fuzzing of stateful, protocol-based applications as well as gui-based (Android) apps.

Prof Bernd Meyer

Visual Tracking of Individuals in Crowded Scenes

The project will explore how far we can push tracking in very crowded scenes using deep learning segmentation and classification combined with advanced optimisation methods.

Prof Bernd Meyer

Ecosystem Monitoring using Deep Learning

The project will develop methods to use acoustic data for the identification of insect species in the wild and in controlled agricultural settings.

Prof Bernd Meyer

The impact of environmental stress on insect colonies - Protecting social insect ecosystem services

This project aims to generate a more complete picture of how environmental factors and stress influence division of labour in a colony and with this the limits of this flexibility. The project builds on evolutionary game theory to develop a new approach for analysing how environmental factors impact on DOL and colony viability. Our work combines mathematical models and computer simulations with biological experiments in the lab and field.

Prof Jon Whittle

Women in STEM Grant

This project is a part of an exciting collaboration with Monash Tech School, Victorian Space, Science Education Centre, micro:bit, Tech Girls Movement, Hacker Exchange and Monash Generator to develop and nurture an entrepreneurial mindset in the next generation of women in the Internet of Things (IOT). We are trying to organize hundreds of teenage girls to learn the concepts of IOT by developing software programs using the hands-on micro:bit devices. This project will explore that how to enhance girls’ learning experience about STEM and how such learning experience can contribute to their future entrepreneurial potential.

Dr Reza Haffari

Multi Modal Medical AI

This study centres on how computer-based decision procedures, under the broad umbrella of artificial intelligence (AI), can assist in improving health and health care. The goal of this project is to develop computational models using text and images (and possibly other data modalities) to help medical experts to improve the quality of patient care.

Dr Reza Haffari

Neural Machine Translation for Low-Resource Languages

The proposed project aims to develop new methodologies for developing NMT systems between extremely low-resource languages and English. Recent advances in neural machine translation (NMT) are a significant step forward in machine translation capabilities. However, "NMT systems have a steeper learning curve with respect to the amount of training data, resulting in worse quality in low-resource settings". This project investigates methods to enable high performing NMT in low-resource scenarios.

Dr Muhammad Aamir Cheema

Location-based Social Networks

This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in three unique aspects: utilizing the geographical locations of queries and social network data to provide more relevant results; acknowledging and handling inherent uncertainties in the data; and exploiting knowledge graphs to produce intelligent search results.

Dr Muhammad Aamir Cheema

Indoor Data Management

In this project, we are interested in developing efficient query processing techniques for indoor location data considering textual keywords associated with objects, and data uncertainty.

Dr Barrett Ens

Nomadic Augmented Reality

This PhD project will explore novel methods for Nomadic Augmented Reality, a class of systems, applications and interaction techniques designed to support field workers with visual information on the go.

Professor Bernd Meyer

Computational Modelling of Collective Decision Making

The project will investigate the mechanisms of self-organised task allocation in insect colonies.

Professor John Grundy

Model-driven engineering for mobile/wearable eHealth applications

This project will investigate new approaches to modelling, designing and generating mobile eHealth apps for phones and wearables.

Dr Li Li

Deep learning for mobile app analytics

This project will explore different deep learning techniques for Android app analyses, e.g., to detect Android malware, to identify common vulnerabilities, or to pinpoint repackaged Android apps.

Dr Joanne Evans

Recordkeeping Analytics for Rights in Records by Design

This PhD project will investigate the creative use of digital and networking technologies that go beyond automating and augmenting aging and antiquated systems.

Professor Sharon Oviatt

Human-centred mobile and multimodal interfaces

The dominant paradigm for interacting with computers now involves new media and multimodal input on cell phones, which involves speech, multi-touch, writing, gestures, images, gaze, and sensors.

There are many more innovative projects led by our world-renowned researchers - get involved and help them pave the way to new technologically advanced practices. Scholarship funding is available for exceptional candidates.

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