CSIRO Industry PhD Program Scholarship
Federation University is pleased to partner with CSIRO and Sonac Australia Pty Ltd to offer a PhD scholarship in mechanical engineering. This is a four-year research training program that focuses on applied research and working with the industry sector. It aims to produce the next generation of innovation leaders with the skills to work at the interface of research and industry in Australia.
Stipend: $45,000 per annum
Project support: a four-year project expense and development package of up to $13,000 per annum
RTP Fee-offset Scholarship: $26,400 per annum
Funding length: 4 years only
Location: Mt Helen Campus
The program includes:
- a six-month industry internship
- professional development training to develop your applied research skills
- supervision by Federation University, CSIRO and Sonac Australia
Scholarship applicants must be eligible to undertake a PhD. Verify you can meet eligibility requirements outlined on the Graduate Research School website. If you are applying for Honours equivalence, please provide detailed information to support your case.
- be an Australian citizen or permanent resident, or a New Zealand citizen
- not have previously completed a PhD
- be able to commence the program in the year of the offer
Applicants should contact Associate Professor Ibrahim Sultan, at email@example.com prior to submitting an application.
Application opening date: Coming soon
Application closing date: 25th November 2022
Commencement date: Successful applicants will be expected to commence in February 2023. However the commencement date may be negitioated by the successful candidate.
Research project outline
Project title: Data-driven robust, explainable AI techniques for process, product quality control, and security in intelligent manufacturing
Quality, productivity, and security are essential elements in an industrial production plant. Even a slight improvement in productivity, e.g., 1%, can lead to gains of Millions in revenue. These elements are dependent on various factors, including process control and automation. Furthermore, these factors are derived from several probabilistic and deterministic parameters that span from raw material collection and transportation to manufacturing. In this 4-year Ph.D. research project, a student will investigate the novel methods to improve the quality (e.g., customer requirements), productivity (e.g., production time), and security of manufacturing by considering data-driven approaches and leveraging robust explainable artificial intelligence/machine learning algorithms for overall intelligent automation. This project is outcomes-oriented, so the data is collected from the actual plant of Sonac Australia Pty Ltd, an animal feed industry, and the proposed control methods and techniques will be leveraged to optimize the actual plant.
The project will focus on the process of blood collection and delivery to the production plant. Despite its importance for the quality of the process outcome, this part of the production cycle does not allow for best control and monitoring as it takes place at slaughterhouses and on delivery tankers. The project will look at ways of automating the initial blood processing in the slaughterhouse in a way which prevents damage to the blood (e.g., premature coagulation, impurities, etc.). Also, the process of pumping blood to and from the transporting tanks will be a target for improvement as it has settings (e.g., pumping flowrate) which impact the quality and productivity of the Sonac processes. The outcome of this project will result in better controllability over the pre-plant processing.
Applicant educational background
- Strong background in process engineering, mathematics, including probability and statistics, programming experience in python, knowledge of ML/AI algorithms and frameworks, and understanding of industrial control systems and SCADA
- Good communications skills and the ability to interact with all levels within an industrial organisation
Supervisor contact details
Name of university supervisors: A/Prof Ibrahim Sultan and A/Prof Feng Xia
Email address: firstname.lastname@example.org
Name of CSIRO supervisors: Dr Chandra Thapa and Dr Seyit Camtepe
Industry - Sonac Australia Pty Ltd
Please note, some projects may still be in contracting phases and there is no guarantee for the position until the formal collaboration agreement between the parties is in place.
Further information can be found on the CSIRO website regarding the CSIRO Industry PhD scholarship program - CSIRO.