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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
counter-example guided planning algorithms for mission and epistemic objectives. Integrate multi-modal agentic AI systems into an orchestration framework. Deliver software artefacts and demonstrators
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formative assessment and personalised feedback while ensuring fairness, accountability, and transparency. The research will explore a combination of algorithmic design, human–AI interaction, and empirical
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development of NeurAID repository perform sural nerve biopsy assessment as required for training of AI algorithms collaborate with other clinicians and AI engineers to facilitate the development of algorithms
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Electronics: Creating next-generation microwave electronics that balance size, power, and performance for handheld platforms. Signal Processing for Embedded Systems: Designing and optimizing algorithms
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environmental sensing. The incumbent will contribute to the development and deployment of real-time correction algorithms and hardware systems, leveraging GLAO technologies in collaboration with ULTIMATE-Subaru
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analysis of data from a Laboratory Information Management System. Key responsibilities will include: Core Scientific Contribute to the coding and development of custom data analysis algorithms and modelling
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Job Reference: 1168098 About the Role: You will play a key role in advancing distributed and adaptive AI methods, focusing on scalable software frameworks, learning algorithms, and orchestration
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compelling content and messaging for social media, website, and e-communications in alignment with Institute branding and audience needs. Monitor analytics, platform algorithms, and audience behaviour
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publicly available datasets; 3) Proposing algorithms aimed at improving the accuracy of human activity detection; 4) Implementing these algorithms, evaluating their performance empirically, and comparing
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of single-cell molecular data. Experience and expertise in ML/AI algorithms for analysis of single-cell genomic data Demonstrated capacity to work collaboratively with researchers across both dry and wet