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Department of Population Health) provides an excellent environment for multi-disciplinary research and teaching and for professional and support staff. We work together to answer some of the most important
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of causal inference and machine learning models linking transport, energy, and environmental outcomes • Conduct advanced econometric and statistical analyses of large behavioural and spatial datasets
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to the development of causal inference and machine learning models linking transport, energy, and environmental outcomes • Conduct advanced econometric and statistical analyses of large behavioural and spatial
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experimental studies. You will also contribute to research publications, collaborative research projects, and the development of future research proposals within a multidisciplinary research environment spanning
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in teaching and mentoring of lab members as needed, and otherwise contribute to overall lab operations and collaborative environment. Because this position involves hands-on experiments and close
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-driven, knowledge-based agentic systems for automated alert triage and investigation in SOC environments, contributing to the AutoSOC platform Build explainable AI models that integrate planning, memory
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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become the next generation of research leaders in your field. As a university we aim to create an environment where everyone can thrive and are proactive in fostering a culture of inclusion, respect and
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to both accelerate the adoption of these core ideas and to further advance them. Building on our Guidance on the Safety Assurance of Autonomous Systems in Complex Environments (SACE), you will conduct and
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research statistical applications. Working Conditions Needs to be able to successfully perform all required duties. Office/research environment; some travel and weekend work is required. UTRGV is a