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bottlenecks in data and system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models
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engineering Construction informatics, and in part related to Building Information Modelling (BIM), ontologies, process modeling, databases, open data standards such as Industry Foundation Classes (IFC), and
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of the following areas and an interest to develop within others: Protein chemistry Enzyme kinetics and kinetic modelling Experimental physical chemistry Electrochemistry Assay development and
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restraint conditions. A key goal is to develop both a sensor system and a prediction model for the short- and long-term deformation behaviour of concrete. These tools will be applied to full-scale structural
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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R Experience with single-cell RNA-sequencing, in particular analysis of data would be an advantage Experience with mouse models and possession of a FELASA B certificate would be an advantage as both
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modelling approaches will also be used to complement the experimental work. The bioprocess engineering team at DTU Chemical Engineering consists of around 10 scientists and engineers. Expertise is available
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enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education
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benefits and a structured PhD training program About the research group You will join the Biomimetics, Biocarriers and Bioimplants group (The 3Bs), led by Associate Professor Leticia Hosta-Rigau at DTU
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privacy guarantees. This PhD project will develop scalable, privacy-preserving coordination models that jointly optimize DER integration, electrified loads, and data-center flexibility — ensuring fairness