Scholarship funded PhD research projects

Scholarship funded PhD research projects

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

Monash IT is currently offering a number of exciting and scholarship funded PhD research projects. We’re inviting applications from high achieving eligible candidates.

Featured research projects

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 John Grundy

Integrated security for smart cities: BAS and IoT – the next frontier

We are interested in Building Automation Systems security that utilize next-generation IOT approaches from the perspective of data security (privacy, secure access and storage, secure transmission and utilization) and control security (authorized access to and control of BAS-based features).

Professor John Grundy

Assessing network vulnerabilities through partial pattern analysis - extending the self-securing software system

This project will investigate techniques to (i) detect particular vulnerabilities; (ii) mitigate them at run-time using appropriate techniques; and (iii) evaluate the efficacy of the detection and counter-measures on exemplar real-world applications.

Professor John Grundy

Using smart contracts to support collaborative Business Process Modelling and Execution

We want to investigate how distributed ledger/blockchain technologies can assist in providing improved support for BPM contract agreement, BPM model development, and to support collaborative, inter-organisational BPM evolution.

Dr Marcel Boehme

High Performance Vulnerability Detection

The PhD student will work on the development of highly efficient techniques for automated vulnerability detection in large software projects.

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 Jon McCormack, Dr Tom Chandler, Dr Vince Dziekan, Dr Matt Butler, Dr Tom Chandler & Dr Misha Myers

Collaborative, interactive, immersive Practice-based PhD projects

Four projects: Virtual Heritage Project, Innovative Use of Contemporary Games Technologies, Ars Incognita – Interfacing Creative Research with Digital Cultural, Creating Digital Cultural and Heritage Experiences in the Public Realm

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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