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languages (C, C++, C#, Python, Matlab), experience with machine learning in robotics or computer vision, a desire to advance resilient, introspective processing architectures in robotics, a desire to work
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Carbon Modelling. This position offers an exciting opportunity to make use of the recent developments in AI and machine learning algorithms by measuring soil properties rapidly over a large area using cost
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science and lipids. Experience with AI and machine learning is preferrable but not mandatory experimental skills on microfluidics, analytical techniques, microscopies (fluorescent, confocal and electron
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on the ground robot for real-time soil property assessment, providing critical below-ground data to complement above-ground phenotypic analysis develop machine learning algorithms for real-time analysis of plant
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oscillations, delta Scuti stars, exoplanets, stellar clusters and associations, and machine learning. We make extensive use of data from NASA’s Kepler,TESS and JSWT Missions, and also have access to ground-based
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machine learning and real-time control fabricate robust instrumentation or photonic components for use at 8m-class and future ELT-class observatories lead instrument development projects, including
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discipline in the school and will retain that position at the conclusion of their headship. Drive the School of Computer Science’s academic teaching, learning, and research outcomes in alignment with Faculty