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with sustainability assessment methods, including life cycle assessment and related modelling approaches, and you have applied these in cases and analysis related to biobased products and the bioeconomy
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others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent frameworks). Hands-on experience with data representation and embeddings, ideally applied
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initiatives (e.g. the International Polar Year 2032-33) Integrating novel tools and methods into research and advice to Greenlandic and Danish authorities, including AI-driven data analysis, process-based
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PhD Scholarship in University Students’ Learning Via Digital Twins of Neutron Scattering Instruments
studies and data analysis with one of the leading groups in the field. Qualified applicants must have: An MSc degree in Physics, Nanoscience, Chemistry, Engineering, or Material Science, or Educational
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carcasses for analysis. Your task will be to explore what we can learn from the beached bird data. Topics include the distribution of mortality in time and space, and among species; causes of death, as
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interested in applicants with experience in either (i) high-performance magnetohydrodynamic simulations or (ii) the analysis and imaging of Very Long Baseline Interferometry data, but outstanding candidates
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on the development and application of computational tools in the project. This includes, first and foremost, computational text analysis to detect shaming and shamelessness in parliamentary debates, party manifestos
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design, field and laboratory-based research is required, including experience with algal culturing, microscopic techniques, photo-physiological measurements, as well as biogeochemical analysis
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ecology, data analysis or neuroscience) In addition, desirable qualifications encompass: Documented research experience in the field of comparative and integrative physiology Experience with environmental
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across biology and physiology with one or more of the fields ecotoxicology, cell and molecular biology, stress biology, population biology, biodiversity, climate change ecology, data analysis