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student, you will focus on mining large Actinomycete genomic, transcriptomic and metabolomic datasets to investigate their transcriptional regulatory network. You will develop and apply the latest
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of organizing processes and their outcomes. Methodologically, we value qualitative research methods highly and often adopt case study, field work methodology or social network analysis. The teaching
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research projects and environmental exchange as part of the PhD education. Opportunity to interact with a wider network of national and international collaborators. Opportunity to develop your own ideas
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months at the Technical University of Munich (Germany), gaining international research experience and expanding your collaborative network. As part of your research, you will: Design responsive-switchable
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, take a 4-6 month external research stay, and grow a network across academia, system operators, and industry. Context and motivation The green energy transition is increasingly digital: it relies
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intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and
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photonic devices. Such quantum devices are central for quantum information networks, quantum computation, and quantum cryptography systems, and lie at the basis of a forthcoming Quantum Internet. We focus
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, international team with flexible work organization and support of individual development. The group is involved in a variety of national and European projects and features a strong network of academic and
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’ willingness and ability to adopt the green energy innovations that are essential to achieving a net-zero society. SMEs’ adoption of clean energy technologies is critical to the green transition. Yet, high costs
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research methods highly and often adopt case study, field work methodology or social network analysis. The three-year PhD programme at CBS gives you the opportunity to conduct research under the supervision