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also build your research profile through publications, grants and supervision within a supportive, high performing lab. What you will deliver: Design and execute in vivo functional assays and genetic
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observations and field data collection. Strong competence in data preparation/analysis/visualization with Python, R, or a similar scripting and visualization language. Experience with high performance computing
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sovereignty, and increasing demand for speed, data capacity, and artificial intelligence require research into radiation effects engineering of complex microelectronics. Advanced high-performance devices used
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networks, high-performance computing clusters, and clinical interdisciplinary collaborations across UT Austin. The applicants will join a collaborative research environment at the Translational AI Excellence
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in Soil. Why Join Us? This is an opportunity to contribute to a pioneering research programme that combines carbon capture, circular economy, sustainable construction materials, and geotechnical
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of Excellence to improve outcomes in HCC. You will oversee the preclinical models of liver cancer and administrative activities, in line with the overall programme. This implies perform and support in vivo work
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prediction of agricultural application system performance. You may participate in laboratory, wind tunnel, field, and computational investigations designed to improve understanding of agricultural application
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) Country Australia Type of Contract To be defined Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within
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susceptibility to myiasis; Design and implement computer vision workflows for analyzing imagery from drone-mounted cameras and other high-resolution imaging platforms; Apply machine learning and computer vision
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of the interactions between building stocks, heat and cooling demand, and electricity distribution networks. They will develop new computational approaches, contribute to the expansion of existing modelling tools, and