13 computer-aided-manufacturing Fellowship research jobs at University of Adelaide in Australia
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industry and government. Reporting to the Director of AIML, the RAIR Centre Director will be responsible for the overall strategic direction of the Centre, engaging with key external stakeholders in
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learning research and development, particularly with a specialisation in such areas as: digital forensics, computer vision, biometrics (face or voice recognition, etc.) and natural language processing
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. Quantitative researcher with experience in primary care. The Discipline of General Practice supports teaching, research, clinical practice and the development of better prevention and public health policies
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actions working on causal AI for a changing world. The AIML at the University of Adelaide is the largest computer vision and machine learning research group in Australia with over 180 members including
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within the University and project collaborators, and significant government and industry engagement. The positions will be attractive to skilled and self-motivated scientists who enjoy leading research
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to an exciting research project on social network analysis and online influence. This position will collaborate with industry partners and academics within the Adelaide Data Science Centre. To be successful you
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Educational Technology in the School of Computer and Mathematical Sciences. The successful candidate will be a researcher in the use of technology to support cognitive and meta-cognitive skills of students
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, breadth and quality of our education and research programs - including significant industry, government and community collaboration - offers you vast scope and opportunity for a long, fulfilling career. It
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the timing, scale, and rate of mammal declines in Australia. They will use critical inferences of past demographic change and high-performance computing to disentangle the ecological mechanisms that were
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closely with an industry partner, you will generate cutting-edge insights into protein structures and protein-ligand interactions using in silico approaches such as bioinformatics, modelling and docking