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thereafter. The PhD project will focus on developing and testing AI-assisted computational workflows for predictions of both ground- and excited-state material properties, with applications spanning
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develops predictive, multi-scale computational frameworks to guide sustainable microbial food production. By coupling data science with mechanistic models, this collaboration between universities, research
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Denmark. The work consists of quantitative research, including developing research questions, conducting theory-driven statistical analyses of longitudinal register data, and, where relevant, linking
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exist. To address this knowledge gap, in the BUG-ID consortium, seven European universities, one research institute, one hospital and six private companies have teamed up. Our consortium will train 15
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they lead to electrochemical failures under low and high voltage bias. The project will also include the development of secondary electrochemical models as digital twins. This PhD project is part of CreCon
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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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basic and applied research within physical, organic, and inorganic chemistry. Technology for people DTU develops technology for people. With our international elite research and study programmes, we
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experience in fieldwork and data analysis to technically oriented candidates with expertise in AI and interactive systems development. Scientific dissemination is expected to focus on leading Human-Computer
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. The inherent substrate overlap between amino acid transporters makes it difficult to find selective inhibitors that can be used to investigate the role of amino acid transporters and to develop inhibitors as
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. You will be part of a team pursuing the development of novel integrated data analysis diagnostic tools that address key challenges in the field of energetic particle physics in fusion plasmas, such as