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. Members of the Infection, Immunity and Inflammation theme teach students at both the undergraduate and postgraduate level and bring their research experience to these teaching programs with the goal
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design
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to the camera about your views on the same topic. Get ready to bring your ideas to life! Consider these pointers for your essay and video: Dive into how AI, machine learning, and automation jazz up moving
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PhD Scholarship Keep military drones hidden from enemies! This PhD develops cutting-edge stealth communication tech so UAVs can coordinate and sense their environment without ever revealing
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Job no:523087 Work type:Full Time Location:Crawley Categories:Student Administration / Support Services Lead high-impact, University-wide learning and teaching initiatives that directly shape a
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. Members of the Infection, Immunity and Inflammation theme teach students at both the undergraduate and postgraduate level and bring their research experience to these teaching programs with the goal
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monitoring approaches (e.g., machine learning, real-time sensing). Sponsorship / work rights for Australia You must have unrestricted work rights in Australia for the duration of this employment to be eligible
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
machine-learning methods to investigate the deep-time controls on copper mineralisation. The role will involve developing reproducible computational workflows, generating predictive maps of copper
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molecule cellular accumulation and compiling a proteome-scale atlas of chemically tractable vulnerabilities. The project will accomplish this by 1) using high-throughput mass-spectrometry and machine
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Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much