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developers and technical standards experts, and the public. The work of this PhD lies primarily in legal analysis and empirical co‑design of principles guiding the development and deployment of AI systems
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causal machine learning, transport behaviour analysis, and residential energy demand modelling to support sustainable urban and energy policy. The researcher will contribute to the design, implementation
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combining causal machine learning, transport behaviour analysis, and residential energy demand modelling to support sustainable urban and energy policy. The researcher will contribute to the design
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statistical methods. Proficiency in Python with libraries like NumPy, SciPy, QuTiP and Matplotlib for calculations, optimizations, quantum simulation and visualization. Flexibility to travel and engage fully in
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of data, you will also develop strategies for the management and analysis of the data using various statistical approaches with a view to understanding how we can ultimately use PAT for advanced process
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advice relating to sectoral emissions ceilings and national carbon budgets. The analysis will draw on established energy system modelling tools representing the Irish energy landscape and will utilise
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management. We are looking for someone with a background in, and passion for, molecular ecology/conservation genetics, with strong bioinformatics/quantitative skills (e.g., in the analysis of NGS data
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, complex quantitative datasets, Experience of quantitative research related to child development, Longitudinal data analysis Additional Information Eligibility criteria Mandatory: *PhD in psychology
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sequencing or draft genome sequence analysis, is highly desirable. Project title: Gut microbiome and health Duration: 12 months, full-time post Please note that Garda vetting and/or an international police
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involve advanced data analysis, simulation, and optimisation to support the development of scalable and policy-relevant energy solutions. Working within an interdisciplinary research environment