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, and maintain the databases and data pipelines that power COMPASS research, integrating large multi-source datasets (including ERCOT and EIA records) into reproducible analytical systems. Conduct
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believes in continuous learning and development Proficient in technical writing and presentation Possess good analytical and critical thinking skills Shows good initiative and takes ownership of work
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for: Conducting research and development on AI-based solutions for automated defect inspection and condition assessment of train components by designing and developing deep learning, computer vision, and machine
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analysis techniques, including stochastic processes and machine learning; expertise in analytical and numerical modelling of gravitational-wave sources, and the astrophysical processes governing
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if required Structuring, populating and analysing decision analytic models Leading the co-production of research with external stakeholders Contributing to the design, conduct and analysis of research under
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to single-cell genomics and gene regulation. We are looking for someone who can work confidently with large and varied single-cell datasets, and who enjoys developing, benchmarking, and testing new analytical
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Schemes of Service: Research Division: Health and Social Sciences Employment Type: Fixed Term As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our
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to methods, measures, and analytic plans for federal (e.g., NIH, SAMHSA) and foundation (e.g., WT Grant, Spencer) submissions. Supervise and mentor research assistants, coordinate with community partners and
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analytical and critical thinking skills Able to build and maintain strong working relationships with people within and external to the university Self-directed learner who believes in continuous learning and
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implement data management and analytics protocols for clinical trial datasets Apply deep learning and AI to time series neuromonitoring data Build and test predictive models using machine learning techniques