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engineered to achieve site-specific intestinal release and accumulation locally in the diseased intestinal tissue. Pivotal proof-of-efficacy will be demonstrated in a large animal model of chronic intestinal
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and security. The ideal candidate will have/be: • A PhD qualification in nutrition or epidemiology or public health or cognate discipline. • Experience of big data from a nutrition
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at the cutting edge of micronutrient research. The ideal candidate will have/be: • A PhD qualification in Human Nutrition. • Deep knowledge of food data, including composition, intake and analysis. • Good
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must have concluded a PhD in Computer Science, Data Science, Artificial Intelligence, Computer Engineering or related area (essential). • The candidate should have a background Data Science/Machine
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professionals to mitigate and adapt to the planetary crisis in their daily practice. Individual studies will include literature reviews using a variety of methodologies, large-scale survey, interview/focus groups
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citizens. The successful candidate will provide a CV with evidence for how they meet the following criteria: · The candidate must have concluded a PhD in Computer Science, Data Science, Artificial
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hunger to improve health in the EU [the Zero Hidden Hunger EU project https://www.zerohiddenhunger.eu]. This large-scale, multidisciplinary project, with 19 partners from 10 countries aims to provide
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professionals to mitigate and adapt to the planetary crisis in their daily practice. Individual studies will include literature reviews using a variety of methodologies, large-scale survey, interview/focus groups