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combination of activities including securing competitive funding at national and European levels, building new collaborations within DTU and with external stakeholders, and initiating high-impact scientific
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assessments. Responsibilities and qualifications The project will contribute to a comprehensive, Cradle-Gate impact database for combinations of feedstock, pretreatment methods and microbial products
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muscle adaptation to exercise, inactivity, and disease. Our research combines genetic and pharmacological manipulation of animal and cell-based models with advanced microscopy, omics technologies, and
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, learning, and shared understanding in blue-collar workplaces. The project combines fieldwork in real-world settings with the design and evaluation of AI-driven tools. You will join an active, collaborative
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this challenge by developing privacy-preserving data-sharing mechanisms and data-driven decision-support tools, and combining them in an end-to-end pipeline for sharing and exploiting high-quality data. A core
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responsible business and governance is organised around various research environments. Further information is available here: https://www.cbs.dk/research/department-management-society-and-communication
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responsible business and governance is organised around various research environments. Further information is available here: https://www.cbs.dk/research/department-management-society-and-communica
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-collar workplaces. The project combines fieldwork in real-world settings with the design and evaluation of AI-driven tools. You will join an active, collaborative team in a supportive research environment
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analysis, and basic feature engineering. Experience with Python or a similar programming language, and basic exposure to scientific computing or machine learning libraries, combined with an interest in
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related to Riemann-Steltjes optimal control to combine PMP with Bayesian Optimisation, allowing for data-efficient learning. You will then implement and validate the new method on simulated fermentations