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to apply your expertise to real-world clinical challenges. To be successful, you will have: Postgraduate qualifications in computer science, data science, or a related discipline (PhD preferred
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Proficiency in analytics, AI, and modern data science tools Excellent problem-solving, project coordination and communication skills A PhD or equivalent research experience (preferred) Experience with clinical
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evaluate methods via experiments, benchmarking, simulation and/or real‑world data. The successful candidate will have: A PhD in Statistics, Data Science, Computer Science, Mathematics, or a related field
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the University’s research capacity in a globally relevant field. The role provides the opportunity to develop and publish a monograph based on Korean Studies-related PhD research or, if already published
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data (e.g. DFT, MP2) and experimental data into AI-driven pipelines for structure–property learning and reactivity prediction. Applying AI models to real-world problems in virtual screening, ligand
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fast-readout electron detectors to validate the methods developed. The successful candidate will have a PhD in Physics, Materials Engineering, Computer Science or a closely related field. Research
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, fabricate structures at the Melbourne Centre for Nanofabrication, and measure their optical and electrical properties. The successful candidate will have a PhD in Physics, Materials Engineering, or a closely
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and contribute to the preparation of manuscripts stemming from your work. If you have a PhD in organic chemistry, ideally with a background in protein chemistry or chemical biology you might be
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, collaborative community Be surrounded by extraordinary ideas - and the people who discover them The Opportunity Are you eager to use data to reduce injuries and create a safer world? Do you thrive in
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focus on financial incentives designed to promote safer and lower carbon driving. In this role, you will contribute to the estimation and extrapolation of treatment effects from trial data, modelling