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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark
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spectroscopy Experience Proven experience in algorithm development to do physiological signal processing Experience in advanced computational techniques to assess and enhance signal quality Experience in machine
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research initiative funded by ARIA, titled Aggregating Safety Preferences for AI Systems: A Social Choice Approach. The project operates at the interface of AI safety and computational social choice, and
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development, human-computer interaction, data analytics, user experience design, remote monitoring systems, energy optimization algorithms, and environmental impact modeling. Human-centric AI-driven sanitation
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Automated Verification theme in the Department of Computer Science and a research group with responsibility for carrying out research on the robustness (continuity) of equivalences in probabilistic systems
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binding pockets. About the role We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to identify domain functional families
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strategy. Knowledge, Qualifications, Skills and Experience Knowledge &Qualifications Essential: A1 SCQF Level 10 (Honours degree) in Statistics/Computer Science or a cognate discipline, or equivalent. A2
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’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. The Department of Women and Children’s Health is a lively and supportive
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. The scope of the research will encompass aspects such as network monitoring, routing algorithms and network-hardware benchmarking. About you You should possess a MSc/MEng in Engineering, Computer