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Job Description If you are passionate about marine technology, data analytics, and ecosystem research, we have an opportunity for you! DTU Aqua invites applications for a PhD position focused on
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characteristics are intricately linked to the electronic configurations of the f -element ions, and any modifications in these configurations result in dramatic changes in their physical and chemical properties
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linked data Sensors as part of Internet of Things (IoT) and integration of sensory information in simulation models as part of Digital Building Twins (DBT) during run-time Life cycle and sustainability
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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optimization of SERS substrates, Raman measurement, data analysis, and validation of results with reference methods such as high performance liquid chromatography (HPLC). You are expected to have a solid
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academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme
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Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our
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the recruitment process here . You can read more about career paths at DTU here . Further information Further information may be obtained from Head of Section Jake Badger jaba@dtu.dk and Professor
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integrating machine-learning techniques with experimental datasets on bioplastic degradability. You will work to establish links between polymer features and degradability through mapping of existing data
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Engineering, respectively, will be important. You are expected to actively contribute to joint research projects, experimental design, and data interpretation across disciplinary boundaries. Responsibilities