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future-focused educational powerhouse that fosters economic and social wellbeing through ground-breaking research and innovative teaching. You can learn more about Adelaide University HERE and more
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training materials for research teams, focusing on data science and machine learning techniques in geoscience. Position description: PD [Research Fellow] [520112].pdf To learn more about this opportunity
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The successful applicant will conduct research to design and develop novel machine/deep learning based trust technologies for securing IoT services/devices. The successful applicant will conduct
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the Faculty, the Department of Electrical and Computer Systems Engineering (ECSE) offers internationally acclaimed programs in power systems, telecommunications, electronics, robotics and biomedical engineering
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days per year Aboriginal Cultural leave 17% superannuation contribution Health and fitness membership options Accommodation and car hire discounts Health insurance and banking Relocation assistance
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, either face-to-face or online (contact centre experience highly regarded) Customer focus and a can-do attitude. Proficiency in the operation of computer applications and the ability to learn new systems
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science, machine learning, advanced computational design, and wearable technologies. To be successful you will need: Completion of a PhD in electrical, software, optical, biomedical engineering or physics
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Levin Kuhlmann Research area Machine Learning We are seeking a highly motivated and innovative PhD student interested in exploring the opportunities for using AI to enhance personalisation of services and
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student experience. You will bring to the role: Proven academic leadership with a PhD and substantial experience in curriculum development, quality assurance, and learning and teaching within a university
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with a range of computer systems and applications, including COVIDENCE and statistical software including R. Experience running and performing meta-analyses or network meta-analyses, including statistics