Mt Helen - PhD (Industry) scholarships
Federation University is seeking PhD candidates for fully-funded projects co-designed and co-supervised by IBM scientists and leading academics within the University’s research centres.
Successful applicants will be based at Federation University’s Mt Helen Campus and will receive a scholarship of up to $40,000* per calendar year in partnership with the Department of Education and Destination Australia.
Successful applicants will also have the opportunity to participate in an industry-based internship.
*dependant on project. Please see 'Scholarship details' in the specific project for more information.
Current project opportunities
These opportunities are open to suitably qualified people with relevant academic qualifications and demonstrated fundamental technical knowledge (e.g. multimedia processing and analytics, machine learning, IoT and data science) relevant to the application domain of each project (e.g. health, engineering and supply chain).
Specific skills and interests relevant for each project are listed below.
Please direct any questions regarding the projects to the first listed supervisor in the project description.
AI/ML approaches for Identifying biomarker via gene association
Description
Biomarkers, as indicators of biological state, mostly refer to physiological or physical phenotypes, and at the molecular level, these can indicate disease-associated molecular changes and may be useful in disease diagnosis, various infections, and for defining therapeutic targets. In proposed studies, data from various omics techniques, including gene expression profile will be considered as useful starting points. Machine learning (ML) trains computational models to learn enormous data for solving a particular problem, such as biomarker identification. Traditionally, for biomarker discovery, AI typically uses classification and feature selection using static gene relationship. In proposed research, apart from this, we will aim to develop novel AI and ML based methods for dynamically identifying biomarkers via an accurately inferred gene regulatory network. We would aim to extend the analysis for accurate repurposing of drugs. Such non-invasive drug repositioning can be at personalised level and will be of immense benefit. The proposed project will develop a highly accurate novel modelling framework using some of the sophisticated AI/ML methods, i.e. Natural Language Processing (NLP) for acquiring prior knowledge by automated text mining, novel data augmentation methods (Generative Adversarial Network) to work within low data regime, designing a novel framework for modelling genetic network.
Supervisors
Federation University: Prof Madhu Chetty, Prof Fadi Charchar
IBM: TBA
Affiliated research centre
Health Innovation and Transformation Centre
Scholarship details
Scholarship amount: $40,000 per annum*, funded by Department of Education and Destination Australia
Fees: Up to $32,000 per annum covered by a Research Training Program Fee-Offset Scholarships (domestic students) or a Federation University Tuition Fee Scholarship (international students).
Artificial intelligence and health crisis support
Description
Traditionally, the crisis support of the health care is via phone, but more recently support is being provided via online chat and SMS text. This research seeks to significantly boost this capacity to rapidly meet the mental health impacts of future crises (COVID 19), through the development of novel artificial intelligence (AI) and machine learning (ML) solutions.
Skills and interests relevant to this project
IT, data science, AI, engineering
Supervisors
Federation University: Associate Professor Madhu Chetty, Professor Britt Klein, Associate Professor Peter Vamplew
IBM: Dr Jonathan Vlahos
Affiliated research centre
Decision support to achieve net zero carbon for land managers and enterprise managers
Description
To meet Sustainable Development Goals, many enterprises aspire to achieve net zero carbon. Working with regional industries, this project uses sensors and artificial intelligence to access the quantity and quality of data for carbon monitoring, modelling, accounting and visualisations, as an evidential base for their claims of carbon neutrality.
Project outcomes will include collaborative development, regional data sharing and the uptake of digital technologies including data federation, visualisation, image analysis, modelling and AI.
Academic background
IT, data science, AI, agriculture
Supervisors
Federation University: Dr Birgita Hansen, Dr Nathan Robinson
IBM: Dr Arun Vishwanath, Dr Ram Kolluri
Affiliated research centre
Centre for eResearch and Digital Innovation
Scholarship details
Scholarship amount: $40,000 per annum*, funded by Department of Education and Destination Australia
Fees: Up to $32,000 per annum covered by a Research Training Program Fee-Offset Scholarships (domestic students) or a Federation University Tuition Fee Scholarship (international students).
Maximising data integration and interoperability for better regional outcomes
Description
Rapid regional change through climate, population and economic pressures is an urgent global issue. This project explores the use of data sharing and modern smart technologies to enhance regional liveability, prosperity, innovation, safety and social connectedness in the rapidly growing City of Ballarat, using data visualisation and analytics to improve planning.
Academic background
Data science, design thinking, smart cities, organisational strategy and Organisational change
Supervisors
Federation University: Associate Professor Helen Thompson, Dr Shoaib Riaz
IBM: Professor Iven Mareels
Affiliated research centre
Centre for eResearch and Digital Innovation
Scholarship details
Scholarship amount: $40,000 per annum*, funded by Department of Education and Destination Australia
Fees: Up to $32,000 per annum covered by a Research Training Program Fee-Offset Scholarships (domestic students) or a Federation University Tuition Fee Scholarship (international students).
Smart Farms: Using big data to improve decision making
Description
The use of agricultural technology, including Internet of Things (IoT) is becoming an increasingly important aspect of management of agricultural businesses. This project would seek to provide models for farmers to utilise IoT, use their own data for decision making and pool data to enable big data modelling at a district and regional level. The very practical outcome of an “agri-data lake” of regional data would add considerable value to farm management and regional wealth creation. This project would include development of broader understandings of productivity to include economic, environmental and social outcomes based on how we collect and understand a broad range of data.
Aim and objectives
Aim of the project is to develop smart decision-making tools that can be used at farm and regional level to improve economic, environmental and social sustainability of agriculture.
The project will specifically address the following objectives.
- Identify shortcomings in handling numerous networked devices at farm and regional level.
- Develop architecture of farm management systems based on IoT using bio-physical, social and economic data.
- Identify governance issues regarding the use of data amongst stakeholders and develop business models to address them.
Student profile
Must have an undergraduate degree in Agriculture, Business, Data Science or a related discipline. An equivalent experience of working in relevant industry can also be considered.
Supervisory team
Principal Supervisor: Professor Harpinder Sandhu
Associate Supervisor: Dr Shoaib Riaz, Associate Professor Shyh Wei Teng
IBM supervisor: Jonathan Vlahos
Scholarship details
3 years stipend to eligible candidate: AUD $30,000 per year for three years (Destination Australia Scholarship plus ARCC funding)
3 months paid internship with a local agricultural research organisation for the PhD candidate: AUD $3,000 per month TBC
Project operating cost: AUD $7,000 over 3 years TBC
Deliverables
- Successful confirmation of candidature (before 12 months of the first anniversary of the starting date)
- Satisfactory annual progress reports in year 2 and 3 of candidature.
- Timely submission of the thesis for examination.
- Annual progress report to industry partner in year1, 2 and 3.
Using data analytics to accurately predict different types of risk within supply chains
Description
A supply chain can be represented as a graph of material, process, and information flows, interacting with the environment. In this PhD project we seek to model such representations from available data with an aim to characterise objectively the associated risks.
Student profile
Must have an undergraduate degree in IT, data science, AI, business or supply chains
Supervisory team
Federation University: Professor Andrew O’Loughlin, Professor Iven Mareels, Dr Taiwo Oseni
IBM: Dr Chris Butler
Scholarship details
3 years stipend to eligible candidate: AUD $30,000 per year for three years
3 months paid internship with a local agricultural research organisation for the PhD candidate: AUD $3,000 per month TBC
Project operating cost: AUD $7,000 over 3 years TBC
Deliverables
- Successful confirmation of candidature (before 12 months of the first anniversary of the starting date)
- Satisfactory annual progress reports in year 2 and 3 of candidature.
- Timely submission of the thesis for examination.
- Annual progress report to industry partner in year1, 2 and 3.
Applications are now open.
Eligibility
Scholarship applicants must be eligible to undertake a PhD. Applicants must verify that they meet the eligibility requirements outlined on the Graduate Research School website before they apply.
If you are making a case for Honours equivalence, in order to demonstrate your eligibility, please ensure that you provide detailed information to support your case.
Applications are open to Australian residents, Australian permanent residents and international applicants.
Conditions
- Students are expected to commit to full-time study for the duration of their candidature.
- Scholarships are for a period of three years and extension to scholarships will not be granted.
- Successful scholarship applicants must reside in or relocate to Ballarat and study on campus.
- Successful scholarship applicants must participate in an internship period.
- Successful scholarship applicants must formally assign, in advance, all rights, title and interest they may have in any IP developed to the University prior to commencing a project.
View the general conditions for Federation University HDR scholarships on the Graduate Research School website. Where these conditions differ to those on this form, the conditions outlined for this specific scholarship take precedence.
How to apply
Applicants who do not complete all steps will not be considered.
Step 1: Follow the application process outlined at: How to apply
Step 2: Provide a 1000-word statement covering the following areas:
Applicants are not required to provide a 250 Project Summary.
Step 3: Complete the Scholarship Expression of Interest Form