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collection, data wrangling, big data analytics, and the application of artificial intelligence and machine learning techniques. The role is focused on data and analytics related to development applications
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. Essential qualifications and experience a PhD (or near completion) in one of the following fields (or a closely related discipline): Computer Science, Artificial Intelligence, or Machine Learning Economics or
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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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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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, in‑forest sensor networks, machine learning and AI to generate advanced digital forest data and operational insights for the Australian forestry sector. You will co‑lead a multidisciplinary research
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, Search and Recommendation, Data Science, Machine Learning, and Big Data Analysis, Distributed Computing and Cybersecurity Human-Computer Interaction. SCT will fast-track digital innovation across all
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development. Demonstrated experience developing applications interfacing with machine learning libraries like PyTorch or ONNX. Demonstrated experience working with large-scale data processing and deployment
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. Details of the role This Data Scientist role offers a unique opportunity to work at the intersection of artificial intelligence, machine learning, and healthcare. The role will contribute to designing and
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 days 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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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 days ago
numerical seismology, data processing, computer programming, and fieldwork are encouraged to apply. The position working with Dr Caroline Eakin will focus on research in observational seismology, with the aim