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field. Have proven expertise in statistical modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in
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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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will research novel methods for effectively working with geometry models of large and complex assemblies in HPC environments to support high-fidelity engineering simulations (e.g. FEA and CFD). This post
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to pregnancy, lactation, and menopause. In this role, you will support a range of projects by managing and analysing data from clinical trials, cohort studies, and large linked administrative datasets. You will
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23 Sep 2025 Job Information Organisation/Company RMIT UNIVERSITY Research Field Environmental science Geosciences Researcher Profile First Stage Researcher (R1) Country Australia Application
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, validate, and refine ReaxFF (or related) force fields against high-fidelity quantum mechanical data and targeted experiments. Automation & High-Throughput Pipelines: Design, implement, and maintain automated
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a focus on data analytics, AI, ML, advanced process control, and digital twin technologies in semiconductor manufacturing. Experience with handling industrial big data problems, physics-informed AI/ML
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motivated candidate to carry out bioinformatic analysis on large genomic datasets, with comparisons to associated metadata. This will include development of analysis pipelines and interpretation of whole
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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data from major facilities, including NASA’s Kepler, TESS, and JWST missions; ESA’s Gaia mission; and large-scale spectroscopic surveys such as LAMOST. Experience working with large, complex datasets is