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precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities. This creates a large loss of value of strategically valuable raw materials and waste of energy related
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in machine learning and artificial intelligence Experience with numerical analysis and scientific computing Knowledge of power systems and renewable energy technologies Experience in power system
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candidates with a degree in materials science, solid state chemistry, electronic engineering or similar. Experience with one or more of the following areas is considered an advantage. Fuel cells and
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relation to the expected loading conditions during the lifetime of a window. Your primary tasks in the PhD project will be to: Identify relevant material and process parameters for characterization of glass
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programme, please see DTU's rules for the PhD education . Assessment The ideal candidate will have solid background in experimental molecular biology combined with experience with microbial protein production
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. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a leading technical university globally
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science applications Computational Atomic-scale Materials Design with a focus on materials modeling and discovery with electronic structure calculations and machine learning Luminescence Physics and