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Field
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Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly of Technology, of Innovation and of
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their evolution during catalytic operation and activation. You will apply advanced electron diffraction techniques (3DED, 4D-STEM tomography), atomic resolution STEM imaging (HAADF, ABF), EDX and EELS
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deep learning, imaging and data analysis would be helpful for this project. Must be eligible to enrol in PhD programs at Curtin University. Application process Please send your CV, academic transcripts
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energy-efficient CMOS blocks implementing SSM-based LLMs. Prototype hardware blocks on FPGA and prepare for ASIC tape-out. Benchmark performance and comparison with transformer accelerators. Work with
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industrial environmental burden of our generation. Disruptive innovations are required for alternative reduction processes that convert mineral ores into metals without today’s carbon-based methods
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materials and energy-intensive manufacturing processes. These machines dominate current electric powertrain solutions but pose challenges in terms of resource supply chain, recyclability, and embedded carbon
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management skills. Candidates with laboratory skills and imaging are desired for this project. Must be eligible to enrol in PhD programs at Curtin. Application process Please send your CV, academic transcripts
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Design and conduct analyses linking vocal biomarkers to validated psychological scales (e.g., PAID, PHQ-9, GAD-7). Apply natural language processing (NLP) and AI techniques to large-scale audio datasets
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PhD Studentship: Towards Sustainable Powertrains: Enabling High Motor Performance without Rare Earth Materials and Energy intensive Manufacturing Processes The University of Nottingham This project
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical