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plant – microbe interaction and mechanistic understandings Strong ability to interpret data and think analytically, critically, conceptually, synthetically and interdisciplinarily Strong social competence
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such as CAPeX. You are an experimentalist - second to none. You have experience in one or more of the following areas: Analytical electrochemistry Vacuum science/surface science MEMS chip design and
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into the enzyme-substrate interaction in the same set of enzymes. Further, there will be collaboration with a PhD student from NTNU working with similar analytical methods on another class of carbohydrate-active
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following qualifications: Programming skills and AI interest Data analytical skills and computer science focus Experiences with chemical analysis and pilot experiments is an advantage. Knowledge
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of prior data?) Additional research topics may include: Algorithmic Transparency and Fairness in Funding Decisions Comparative Analysis of Funding Models AI-Driven Predictive Analytics for Funding Success
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experiments, and parametric investigations. The modelling component will be based, as much as possible, on semi-analytical thermo-mechanical formulations. This is to facilitate calculation accuracy, numerical
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, mathematics, computer science or similar; Solid mathematical and analytical skills, including signal processing, optimization, or information theory; Experience in programming, e.g., in C++, Python or Matlab
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experience should cover basic chemistry analytical skills to large scale pilot experience, hands-on, and data analysis. This includes experience on corrosion, kinetics, emission impurities, and solvent
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Foundation Center for Biosustainability (DTU Biosustain) Recent progress in our ability to read and write genomic code, combined with advances in automation, analytics and data science, has fundamentally
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on a panel of selected test bacteria and culture methods underestimate the biocide tolerance of Campylobacter . Your primary tasks will be to: Collect existing data regarding the biocide tolerance