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carbon, nitrogen, and water flows in agroecosystems. A solid background in uncertainty quantification, applied statistics, Bayesian calibration, and Monte Carlo simulations. Strong skills in scientific
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grant project “Driving innovation in crop resilience through Comparative QTLomics.” The selected candidate will contribute to five main objectives: 1. Apply large language models (LLMs) to collect
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computer science, explainability is mainly evaluated through data-driven metrics. While they provide some insights for developers, it is unclear whether existing metrics track any ethically relevant properties
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organisations and institutions Furthermore, applicants who can document the following will have an advantage: a basic understanding of the Danish VET system a track record of research publications of a high
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strategies and market positioning. Job description The successful candidate is expected to contribute to the overall objectives of the project by being involved in design, implementation, data collection, and
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modelling, or live neural imaging is desirable Experience working with neurons and knowledge in neurobiology is desirable Track record of international mobility is highly valued Publication record is
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using the COM-B model and Behaviour Change Wheel across three phases – baseline measurement, pre/post pilot assessment, and longitudinal tracking. Collaborating with technical partners (e.g. on digital
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Innovator Grant from the Novo Nordisk Foundation and carried out under the supervision of Professor Claus Elsborg Olesen. The project’s main objective is to optimize the RNA delivery platform through in vitro
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comfortable performing in vivo studies (FELASA-B certification or an equivalent qualification is an advantage); have a documented track record of scientific publications or demonstrate strong potential
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design. Experience working with sustainability and circular economy initiatives in a private-sector context. A strong track record of participation in interdisciplinary research and innovation projects