New Energy Research Scholarships

Federation University is seeking PhD candidates for fully-funded projects designed by leading researchers from the Centre for New Energy Transition (CfNETR). Successful applicants will be based at Federation University’s Mt Helen Campus

Applications are currently open to domestic, Australian permanent residents and international students and close on Sunday 15th January 2023.

Current project opportunities

These opportunities are open to suitably qualified people with relevant academic qualifications and demonstrated fundamental technical knowledge relevant to the application domain of each project

Specific skills and interests relevant for each project are listed below.

Applicants with questions regarding these PhD positions and scholarships, can contact the Director of the Centre for New Energy Transition Research (CfNETR), Professor Nima Amjady, at

Forecasting impacts of weather and climate extremes on renewable energy sector using data mining and machine learning approaches

Forecasting impacts of weather and climate extremes on renewable energy sector using data mining and machine learning approaches

Human-induced global warming is already affecting weather and climate extreme events in many regions world-wide at a rate that is unprecedented in at least the last 2000 years. In Australia, we are exposed to just about every weather- and climate-related hazards annually, ranging from severe thunderstorms, tropical cyclones and devastating floods to extreme bushfire and heatwave events. Over recent years, these extreme events are observed to occur in multiple combinations – occurrence of such multiple events simultaneously are often referred to as compound extreme events – causing widespread risks to various sectors including, but not limited to, socio-economic, environment and infrastructure. With future projections of increased level of greenhouse global warming, risks associated with compound weather and climate events in Australia are very likely to exacerbate.

Energy sector is no doubt highly vulnerable to climate change impacts, particularly through changes in frequency and intensity of extreme weather and climate patterns. Weather-driven volatility and intermittency of wind/solar power pose several challenges for the operation and scheduling of wind/solar farms as well as power systems. Effective renewable energy forecasting is a crucial solution method to alleviate the adverse effects of renewable energy volatility. However, the time series of renewable energies, such as the time series of wind and solar powers, typically exhibit nonlinear behaviours, outliers, and irregular patterns. To appropriately model these complex behaviours, as well as incorporate intermittent behaviours of weather and climate extremes, a renewable energy forecasting method should be able to effectively extract the informative features of the forecast process and construct the input/output mapping function of the renewable energy. In addition, the single-point forecast, which has been traditionally used in power systems (such as in load forecasting), may not be sufficient for the prediction of renewable energies as diverse realizations of a renewable energy, which are different from the expected value, can occur in practice.

To address the aforementioned issues, a renewable energy probabilistic forecasting method, based on data mining and machine learning methods, will be developed in this project. Data mining methods, such as those based on mutual information, will be used for selecting/extracting informative features of the forecast process. These input features are given to a forecast method (such as a deep neural network), which is trained by machine learning methods. In addition to point forecast, probability distribution of renewable energy will be also predicted in this project. The forecasted probability density function can be used both for defining renewable energy scenarios (which can subsequently be used for the operation of wind/solar farms and renewable energy-integrated power systems) and for predicting the impacts of extreme weather conditions (such as the tails of wind speed/power density function that can be used to predict the impacts of thunderstorms and hurricanes on wind farms and wind power-intagrated power systems).

Dr Savin Chand: My accomplishments in Research have always been meritorious and award-winning throughout my academic career at FedUni. In 2017, I was awarded the Vice Chancellor’s Award for Research Excellence for leading world-class research in the research discipline area of “weather and climate extremes”. I continued to excel in these areas through my cutting-edge research with leading scientists from around the world. Very recently, I published a paper entitled ‘declining tropical cyclone frequency under global warming’ as a lead author in the prestigious Nature Climate Change journal. This work received a huge media coverage and scientific recognition globally. I have also received around $570k of external research grants as a Lead Investigator in the last five years, including over $180k during 2022 alone and have also published extensively in top-tier journal in the field. Currently, I am supervising five PhD candidates (three as Principal Supervisor).

Nima Amjady is currently working as Professor, Renewable Energy Technologies and Director Centre for New Energy Transition Research. His research interests include power system operation and planning, microgrid operation and planning, forecast processes of power systems and microgrids, renewable energies. He is a Senior member of IEEE, PES liaison editor for IEEE Press, Editor of IEEE Transactions on Power Systems, Editor of IEEE Transactions on Sustainable Energy and Editor of IEEE Power Engineering Letters. He has extensive supervisory experience of more than 20 research staff/students.

Syed Islam is currently the Associate Deputy Vice Chancellor (Research and Innovation) and previously the Executive Dean for the Institute of Innovation Science and Sustainability at Federation University Australia. He was the John Curtin Distinguished Professor in Electrical Power Engineering and the Director of Centre for Smart Grid and Sustainable Power Systems at Curtin University, Perth, Australia. He is a Fellow of the Engineers Australia, a Fellow of the IEEE and IEEE PES and a Fellow of the IET. He has supervised more than 20 research staff/students to completion.

Scholarship details

Scholarship amount: $29,863 per annum*, funded by Federation University Australia and industry partners

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).

Applications are now open.


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.


  • 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 study on campus in Ballarat.
  • 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 copy of your CV and a 1000-word statement covering the following areas:

    • Discuss your motivations for applying for this PhD scholarship, and your intended research outcomes (both for yourself and for the center)
    • Discuss some of the key existing research literature which impacts this topic area
    • Discuss your relevant research background, experience and outcomes as they are relevant to the project
    • Discuss your plan/proposal to run the project along with the required facilities (hardware, software, etc.)
    • Discuss potential challenges and how you might overcome them

Applicants are not required to provide a 250 Project Summary.

Step 3: Complete the Scholarship Expression of Interest Form