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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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products under different operating conditions. Testing new bioreactor configuration for carbon dioxide biological conversion. Modelling carbon dioxide fermentation to acetic acid. Contribute as teaching
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of this position will be the investigation of meteorological phenomena impacting the wind energy sector, in particular with respect to wind resources and wind conditions. For example, investigating how large-scale
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to be cost competitive with other technologies, long lifetime of >5 years operation under high current density is desired. Operation conditions such as temperature, gas composition, current density 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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allocation, start-up/shutdown sequences, and operational planning of PtX systems in response to dynamic market and process conditions. System Integration and Digital Twin Development: Combine experimental
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to the PhD project ie. processing and analysis of dietary intake data, statistical analyses (eg. linear mixed models) as well as evaluation of child growth and body composition data. Relevant publications
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research in the field of modern high voltage polymer electrolytic capacitors, develop models for lifetime prediction, methods to predict and test for reliability, understand physics of failures at elevated
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will be involved in exploring the models, designing, and measureing CMOS-based interface (coherently control, readout, and biasing) to quantum bits: Conduct a thorough review of recent research in
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of computational chemistry. Applicants can have a background from cheminformatics including RDKit, machine learning applied to chemistry, and molecular modeling Our group and research- and what do we offer? Our