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) and of open science and FAIR practices (through software, datasets and other research outputs, participation in challenges etc). Familiarity with semantic technologies and neuro-symbolic AI, in theory
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software, datasets and other research outputs, participation in challenges etc). Familiarity with semantic technologies and neuro-symbolic AI, in theory and practice, is a firm requirement. The post is full
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responsibility is to test key assumptions about differential disease risk by integrating high-resolution socio-ecological, environmental, and novel health data from individual and population sources. This research
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the Centre’s wider ethos of coproduction. Using your experience in quantitative data analysis, you will examine the links between mental distress and work, care and welfare. You will take forward some selected
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frameworks into mathematical models of complex cross-scale disease dynamics across different epidemiological scenarios. A key responsibility is to test key assumptions about differential disease risk by
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responsibility is to test key assumptions about differential disease risk by integrating high-resolution socio-ecological, environmental, and novel health data from individual and population sources. This research
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in interdisciplinary and international teams. Track record of doing research in diverse international settings. Proficiency in analytical and statistical software. Excellent networking and partnership