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Science, Computer Engineering, Informatics, Data Science, Computational Social Science, or adjacent disciplines with research experience in agent-based modelling, social data science, or social network analysis and
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interdisciplinary study that will assess the pre-/and post-radon concentrations following deep energy-retrofits scenarios of the large-scale national renovation strategy. INFORM will utilise a building physics model
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concentrations following deep energy-retrofits scenarios of the large-scale national renovation strategy. INFORM will utilise a building physics model (CONTAM), which will be parameterised based on representative
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for the analysis of nonlinear phenomena in adaptive dynamical networks with applications to restoration ecology. Adaptive dynamical networks are mathematical models of coupled systems where both the systems
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, Mathematical Modelling and Self-Learning Systems, and Data Science and Analytics as well as a strong PhD programme. The Mathematics Group comprises nine permanent members of staff working across the areas
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-clinical models. They will coordinate and participate in network collaborations to investigate tissue-resident immunity and protection against challenge. They will work closely with an experienced graduate
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of findings across project work packages, contributing to the development of assessment frameworks, modelling inputs, and design optimisations. • Prepare scientific manuscripts, project deliverables, and
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activity in inflammatory bowel disease and test the isolates in pre-clinical models. Prior experience with culturing of anaerobic bacteria is essential for this position. Project Title: Characterising
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and opportunities for just transition in the food and fashion industries and examine job quality and conditions in these industries. This will be followed by behavioural experiments to test policy and
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of the work will be on working conditions, job quality, organisational democracy and social dialogue in the social economy care sector. A key task will be to conduct an online EU-wide survey of working