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methods will relate regional imaging and binding measures to cell-specific gene expression and intracellular signalling. Experience with stress-related behavioural models, particularly chronic social defeat
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-domain, finite element, or method of moments, and you use these tools to translate ideas into robust antenna concepts. It is natural for you to work with advanced antenna architectures, for example
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these methods across different crops to identify conserved patterns of stress resilience 4. Identify candidate genes associated with key agronomic traits related to resilience 5. Contribute to software and web
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-4DµXRD results. Implementing crystal plasticity finite element models that use the experimental data as input and to understand the observed local strain heterogeneities You will work in close
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materials. Use molecular dynamics, lattice-dynamical methods and statistical sampling to investigate local disorder, phase stability, temperature-dependent behaviour and structure-property relations
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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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, vegetation-plot, remote-sensing or environmental datasets; knowledge of climate and land-use scenarios, including SSP/RCP-based projections, and methods for propagating or quantifying model uncertainty
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, glucose tolerance tests, tissue collection). Be motivated to learn and apply advanced mass spectrometry approaches or novel microphysiological methods. Possess or be willing to develop coding skills (R
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. The position is a two-year role and funded by a DFF research project (‘Safeguarding Users’ Cognitive Autonomy in Human-AI Interaction’). Research objectives This project develops methods to detect changes in
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in using natural language processing (NLP) methods on large-scale text data. Candidates with substantial experience in NLP and text-based analysis will be particularly well suited to the project