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sustainable materials, (d) Artificial Intelligence (AI) models to predict and control the manufacturing process and (e) a Digital Twin (DT) incl. Building Information Modeling (BIM) information backbone
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. The areas of responsibility include: Develop computer vision and AI models for detecting wind turbine blade damage and predicting its progression, with experimental validation carried out at DTU test
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to plastic pollution and a circular plastic economy. Responsibilities and qualifications Your activities will revolve around the development of a framework to predict the degradability of bioplastics by
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modelling, and prediction tools. Fouling Control Coatings Fouling Control is performed by specifically designed materials to remove or prevent biofouling from i.e. ship hulls, as bio fouling leads
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subsequent impose a risk for humans (One Health). The overall aim is to establish the scientific basis for predicting how interventions in antimicrobial usage in animal production influence the occurrence
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Job Description Are you excited about developing advanced models and algorithms to better understand and predict human decision-making? Are you interested in integrating behavioural models with
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technologies of the department, e.g., batteries and catalysts. The project includes collaboration with experimentalists at DTU, who will verify the computational predictions as well as Saltfoss Energy, our
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dedicated to developing prediction models governing TCR interactions. However, overall the accuracy is limited, and characterizing and predicting these interactions remains a significant challenge. This, we
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structure, food-web productivity and carbon export, neither to quantify or predict it. Your PhD targets this knowledge gap: The interaction between the physical environment and the base of the food web at
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. The core focus of the PhD project will be on staffing and shift scheduling problems, including behavioral aspects. Additionally, strategic layout planning and the prediction of patient pathways are topics