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candidate for a 3-year, fully-funded PhD project. In this research programme, the PhD student will apply state-of-the-art synthetic biology and genome and metabolic engineering to enable environmental
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candidate for a 3-year, fully-funded PhD project. In this research programme, the PhD student will apply state-of-the-art synthetic biology and genome and metabolic engineering to enable environmental
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) of developed bio-based technologies. We aim to develop computational tools that provides insights to guide the research community in DTU and beyond to assess the sustainability of bio-based products. Our work
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, a Ph.D. stipend is available within the general study program. The Ph.D. stipend is for 3 years. The workplace is at the Department of Chemistry and Bioscience in Aalborg, where you will become part
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deficiencies in Europe as diets shift toward more plant-based foods. For MICROSUNSET we will recruit 12 highly talented DCs, whose collective research will focus on bio-accessibility and bioavailability
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sources of quantum light for optical quantum computers. The project takes place in the Quantum Light Sources group at DTU Electro, where we design, model, fabricate and test sources of single photons
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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 . Assessment The assessment of the applicants will be made by Asso
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reproducible research, collaboration, and knowledge sharing. You should meet the following qualifications: A PhD in Electrical Engineering, Robotics, Computer Science, Artificial Intelligence, or a closely
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PhD scholarship in Mid-Infrared Frequency Comb Technology for High-Sensitivity Sensing – DTU Electro
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 . Assessment The assessment
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Do you want to be part of a young, dynamic research group working on designing the next generation of sustainable energy materials using computational chemistry and machine learning? And do you see