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As a pregnancy approaches term (the point at which the foetus is considered fully developed), decisions are made about the timing of birth and the way babies are born. These decisions are incredibly challenging for clinicians and pregnant women. Digital health records, advances in big data,...
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technologies will affect them. It is our anticipation that the work will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly
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for drug discovery. Publishing peer-reviewed research and contributing to industrial software tools. About You To be successful in this role, you will have: A PhD in machine learning, computer science
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surrounded by extraordinary ideas - and the people who discover them The Opportunity If you are a current Monash Master’s or PhD student and can work 3 days per week, the Monash Research Office has
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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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hold a PhD or equivalent experience in Pharmaceutical Science, Chemistry (Analytical, Medicinal or Pharmaceutical) or a related discipline from a recognised university. Experience with a range of
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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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-offs between the modularity (henceforth interpretability) and the efficiency in existing end-to-end modular autonomous driving models. In this PhD project, student is expected to conduct research in
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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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Short description The PhD project is focused on recommended design and engineering principles of totally renewable microgrids with the ambition to outperform traditional networks reliability