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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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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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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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theory, ergodic theory, differential geometry, data science, and/or machine learning. Implement algorithms that efficiently analyse dynamical systems arising from idealised models or data. Collaborative
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planning algorithms for GPS-denied lunar environments and extreme operational conditions stochastic optimisation frameworks for mission-critical decision-making under uncertainty Research areas and technical
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the prediction of molecular crystal structures, their growth and their properties in close collaboration with fellow team members. Developing algorithms for efficient sampling of candidate crystal structures and
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algorithms and techniques and design, implement, test, and maintain software/tools embodying those methods. You will prepare and submit grant proposals to external funding bodies. This position will also
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validation of advanced algorithms for disease detection, contributing to Australia’s data-driven crop health monitoring systems. This work will support sustainable crop production and enhance national
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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning algorithm for photovoltaic applications and utilising them for the investigation
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-based hail climatology for France, Switzerland and Northern Italy, including hail swaths per event across more than a decade. Design, develop and train geostationary satellite-based hail algorithms using