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embeddings, and developing explainable AI methods that translate model outputs into interpretable visualisations for clinicians and chemists. Extending methods to high-resolution MALDI (MALDI-2, timsTOF) and
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, or other participatory research methods is welcome but not required. Experience with food consumption, sustainability, or circular economy research is an advantage but not a requirement. Note that you do not
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already have used data-driven computational methods to model cognitive or behavioural change in any substantive domain, that would be ideal. Experience specifically with research on consumers or citizens
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; survey design and online experimental methods; quantitative data analysis, preferably including choice modelling, willingness-to-pay analysis, segmentation, multivariate statistics, or related methods
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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
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and work in the interface of basic cellular biology /virology and experimental clinical medicine trials meeting the challenges of developing methods to the highest international scientific standards As
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instruments, with data obtained with DNA methods and data obtained with a Hirst trap. • Numerical models used by the group covers the particle dispersion model HYSPLIT in combination and the numerical models
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candidate will have an existing research profile that uses ethnographic methods to explore questions relevant to the social and ecological effects of livestock and agricultural infrastructures on landscapes
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genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods
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-novation, value creation, stakeholder engagement, and the development and validation of methods and tools for circular transitions. Your Profile We are looking for a candidate who has: A PhD degree in Design