PhD Scholarship: Intelligent Battery Management Systems

Job Description

PhD Scholarship: Intelligent Battery Management Systems Churchill, West Gippsland & Latrobe Valley VIC Federation University Australia Gippsland Campus, Churchill VIC & Clayton VIC Research & Fellowships (Science & Technology) $46,000 per year stipend (2024 rate, indexed annually) Advance your career in renewable energy and battery management through the prestigious CSIRO Industry PhD (iPhD) Program. This four-year applied research program bridges academia and industry, equipping PhD candidates with high-level research skills and industry experience to drive innovation in battery intelligence systems. Federation University, in partnership with CSIRO and Techplus Control System Pty Ltd, is offering a fully funded industry PhD scholarship to develop deep learning models and data analytics techniques for enhancing battery management systems (BMSs). This research project will contribute to the renewable energy sector by improving the reliability and resiliency of battery storage solutions. These scholarships enable you to: Earn a competitive stipend of $46,000 per year while conducting impactful research in renewable energy. Work closely with leading researchers from Federation University, CSIRO and Techplus Control System Pty Ltd. Gain industry experience through a three-month internship at Techplus Control System Pty Ltd. Access a structured professional development and training program to enhance your applied research skills. Receive a project support and development package of $13,000 per year for research expenses. The scholarship includes: A stipend of $46,000 per year for four years (indexed annually) Project support funding of $13,000 per year for research-related costs A fully funded PhD tuition fee offset scholarship. A three-month industry placement with Techplus Control System Pty Ltd. Access to cutting-edge facilities and research expertise at Federation University, CSIRO, and Techplus Control System Pty Ltd. Research project Bringing intelligence to battery management systems through a cloud platform As the world transitions towards zero-emission renewable energy, batteries play a vital role in energy storage. However, current battery management systems (BMSs) lack intelligence and advanced condition monitoring capabilities. This project aims to develop innovative deep learning models and data analytic techniques, hosted on the cloud, to enhance fault detection and prediction in BMSs. By leveraging cloud-based computing, the project will create a system that enables real-time analysis and decision-making, ultimately improving battery lifespan and efficiency. This project will: Develop advanced machine learning algorithms for real-time fault detection and predictive maintenance Utilise cloud-based platforms for scalable data storage and analysis Generate actionable insights to optimise battery performance and safety Contribute to the growth of renewable energy by improving battery reliability and resilience. To apply for this scholarship, you must: Be an Australian citizen, Permanent Resident, or New Zealand citizen Be able to commence the program in 2025. Ideal candidate skills A research degree (Honours or Masters) in computer science or electrical engineering, with a focus on machine learning Excellent problem-solving and communication skills Ability to collaborate with academic and industry stakeholders. Experience in power systems or battery technologies Industry experience related to renewable energy or battery management A track record of publishing in high-impact journals. Supervisory team Federation University supervisor: Dr Joarder Kamruzzaman – Institute of Innovation, Science and Sustainability Include a 250-word personal statement on why you are the ideal candidate for this project. Applications will be assessed by the supervisory team, and shortlisted candidates will be interviewed. A formal PhD admission offer will be issued upon meeting all requirements. For specific project-related queries, contact the nominated supervisors above. This is an exciting opportunity to work at the cutting edge of AI and battery management systems, contributing to the future of renewable energy storage. Apply now and be part of a world-class research and industry collaboration! #J-18808-Ljbffr