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proficiency and appetite for energy transition analysis and policy-relevant, multi-disciplinary research. Direct experience with energy systems models is required, and candidates experienced in energy systems
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distinct cohort, in addition to refining how we collect and analyse these data. This project will involve working with existing large datasets, optimisation of data processing and statistical analysis
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available for the various technologies at several sites. The role includes undertaking extensive literature reviews and critically analysing power demands and opportunities for ocean energy technologies while
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-economic analysis complexity and functionality of the tool in co-operation with the ORE Group techno-economic model development group. Project Title: MaREI Post Duration: 12 Months Salary: €53,770 - €58,479
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handling, computational biology such as RNA sequencing and metabolomics and analysis of large datasets will be highly valued. The appointee will work directly with the Aburto Lab group. Our work focuses on
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includes analysing the economic feasibility of the proposed processes (WP1-5) using the Techno-Economic Assessment (TEA). Outcomes will be assessed through a sensitivity analysis as well as a risk analysis
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are also investigated. Work includes for desktop analyses such as chemical kinetic modelling, process simulation, geographic specific bioresources, Life Cycle Analysis, sustainability analyses, techno
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the design and delivery of other data yet to be collected, such as citizen focus groups, as well as the analysis of this data. Application materials: Cover letter (max 2 pages), Including Writing sample
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. - statistical and machine learning techniques for data analysis - atmospheric chemistry research - materials chemistry research - designing and conducting experimental test procedures. Achievement
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this lacuna through comprehensive analysis across multiple in-reach services. The post-doctoral researcher will achieve this through the voices of the service users and staff in addition to other stakeholders