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These supplementary scholarships (top-ups) are funded by the Australian Research Council to support 2 full-time PhD students who wish to undertake research in the field of battery recycling: Project
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) and complete any other CSIRO requirements. Ideally, the applicant will have a bachelor degree in chemistry, chemical engineering, material science or engineering or relevant fields. Preference will be
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Scholarship Melbourne Social Equity Institute Strategic PhD Scholarships Application is required. Check eligibility Key scholarship details Application status Open for applications Applications open
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AI & Cyber Futures Institute - Charles Sturt University | Bathurst, New South Wales | Australia | 5 days ago
Herbicides PhD Student Scholarships: Integrated Australian Shorn Wool Production Forecasting System Using Digital Twin Technology PhD Student Scholarships: Artificial Intelligence-Powered Climate Resilience
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Join the Centre for Quantum & Technology Theory Full-time, fixed-term position at our Hawthorn campus Scholarship stipend About the Role The Centre for Quantum Technology Theory (CQTT) invites
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Centre for Quantum Technology Theory (CQTT) Full-time, fixed term (3 year) position at our Hawthorn campus Annual stipend $34,700 About the Role We are seeking a highly motivated and talented PhD
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English language requirements enrol as a full time, internal student (unless approval for part-time and/or external study is obtained) a master’s or honours degree in Materials Engineering, Physics, or a related
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Materials from Spent Lithium-Ion Batteries”. The PhD research projects are important part of an ARC Linkage Project which aims to develop scalable processing techniques for the regeneration of cathode
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We are seeking one outstanding candidate for a PhD scholarship to work on a project entitled: Human-Centred AI EdTech: Promoting Reading Engagement and Emotional Well-being in Children
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the area of structural health monitoring of civil engineering structures on an Australian Research Council Future Fellowship project “Innovative Data Driven Techniques for Structural Condition Monitoring