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Field
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the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
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, laying the foundations of next generation machine learning. We do this by combining the mathematical and computational cultures, and the methodologies and theories, of statistics, logic, language
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the results of this project. Candidates must possess a good first Degree (or Master's) and PhD (or near competition) in Engineering, Mathematics, Physics, Computer Science, or related disciplines. Your working
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the financial sector. Regular progress reports and presentations to both AIML and CommBank stakeholders. To be successful you will need: A PhD in Mathematics, Computer Science, Engineering or other Machine
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), MEng/MSc (Research Associate) in Electrical Engineering, Computer Science, Statistics, or other related fields. Solid Mathematical skills. Experience in one of the programming language – Python, Matlab
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Research Collaboration (MQ Collab), a three-year research program focused on advancing Road Transport Psychology and Road Transport Safe Systems. With over 30 staff and postgraduate scholars, the key areas
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, and publish high-impact research. Engage with industry and government, contributing to governance and promoting inclusion and diversity. About you PhD qualification in Computer Science, Data Science
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they will need in an increasingly disrupted and challenged world. The Research Fellow will be located in the MAIC-QUT Road Safety Research Collaboration (MQ Collab), a three-year research program focused
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for databehandling: Cloudflare - Personvernregler for databehandling Utløpsdato: Session Navn: _cfuvid Leverandør: .hsforms.com Databehandlingsansvarlig: Formål: Saves the selected language for the website. Utløpsdato
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the Medical Research Council. The Research Fellow will be using Natural Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of