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Field
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for 2D amorphous carbon films in ultralow-k dielectrics, interconnect integration, diffusion barriers, magnetic media, and protective coatings. • Analyse industry bottlenecks and define how MAC
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innovation projects into SMEs across the border region. Essential Qualifications PhD in Electronic Engineering, Telecommunications, Computer Engineering or a related field or exceptionally, equivalent
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environment including supporting competences from colleagues working in the domains of components, microelectronics, data handling and flight software. Technical competencies Knowledge relevant to the field
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algorithms. Design and develop robust Python APIs for edge-only, cloud-only, and edge-cloud computation offloading algorithms. Set up network testbeds integrating hardware, software, and communication
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, research staff, and PhD students. Our members develop both foundational methods and practical systems, with recent research covering areas such as large multimodal models, generative intelligence, 3D content
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) as Art Historical Tool Network Analysis and Cultural Data Human–AI Collaboration in Art Historical Interpretation Digital Provenance Research and Collection Histories Computer Vision for Art Historical
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Bachelor’s degree in Computer Science, Electrical/Electronic/Software Engineering, or a related field. A Master’s or PhD degree in relevant areas will be advantageous. Familiarity with the following areas is
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methods and deep learning to enable scientific reasoning. Develop software prototypes for automated research workflows that integrate autonomous discovery pipelines with modern deep learning architectures
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Fellow to contribute to the CSIRO AR-PST Stage 6 project, Smart Inverters for Voltage Support in DER-Rich Distribution Networks , led by Professor Frederik Geth and Associate Professor Archie Chapman
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• A PhD degree in Materials Science, Chemistry, Chemical Engineering, Physics, or a related field. Candidate who is in the final stages of PhD studies (i.e. submitted thesis; pending oral defence