81 evolution "https:" "https:" "https:" "https:" "https:" positions at Technical University of Denmark
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our group, have shown that luminescent centers in hBN are excellent candidates for the development of future light-based quantum technologies working close to or at room temperature. In the Quantum
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stimulating research environment with excellent opportunities for professional growth and development. The successful candidate will have access to state-of-the-art experimental facilities and resources to help
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role will be vital to the success of the newly established DTU Arena for Life Science Automation (DALSA; https://dalsa.dtu.dk/ ). Together with a multidisciplinary team, you will implement DALSA’s
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operational efficiency. Key objectives include the development of a tailored risk-based inspection (RBI) and risk-centered maintenance (RCM) model to address specific vulnerabilities in wind turbine components
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development of deep learning tools applied to different types of genomic data, proteomics, expression data, immune profiling, metabolomics data, or general health data. You will have a proven track record of
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Job Description Are you passionate about microbial cell factory development and eager to build your career as a scientist? Join our DNA Foundry team, part of the BRIGHT Biofoundry, where you will
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), we are seeking an excellent and highly motivated PhD candidate to work on exploring connections between quantum mechanics and gravity, in particular on theoretical development of potential low-energy
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for the DigiWind project: https://digiwind.org/ , with a primary focus on DTU Wind’s DigiWind course portfolio: https://www.dtu-digiwind.org/ . The profile we are looking for have strategic communicator- and
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conventional agriculture-based alternatives. This project will pioneer the development of a high-resolution assessment framework that will revolutionize biotechnology by developing comprehensive computational
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conventional agriculture-based alternatives. This project will pioneer the development of a high-resolution waste-derived novel biotechnology feedstock-host background data generation to enable sustainability