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validation to industrial deployment, while continuously strengthening the CORC Development Model through practical implementation. Key responsibilities include Lead the development and implementation
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of Things (IoT) systems. More details about the project can be found at the end of the announcement. TEGnology develops thermoelectric battery-less sensing solutions targeting long-term, maintenance-free
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Biological Section and the Centre for Gelatinous Plankton Ecology & Evolution, lead by Senior Scientist Dr. Cornelia Jaspers. The postdoc is funded via the Danish Research Council and the DFF2 project - Marine
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Assistant Professor in statistics for the development of privacy-enhancing techniques in health care
substantial potential to improve diagnosis, prognosis, and treatment across a wide range of diseases through data-driven analytical approaches. Progress in developing robust methodological frameworks relies
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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness
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with multi-nature sensing data from optimally chosen locations Development and application of advanced fracture mechanics models for crack initiation, growth simulation and remaining fatigue life
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is the development of hybrid models that combine our integrated national model of Denmark with AI-based methods to improve predictions of floods and droughts. We seek to enhance our ability to predict
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drought early warning and monitoring system for large-scale river basins. The project will explore both data-driven and model-based approaches for drought predictions, paving the way for a continental high
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Two DTU Tenure Track Assistant Professors in Autonomous Modelling and in Robotic Synthesis of Ene...
, automated experimentation, advanced characterization, and data-driven decision making. We seek outstanding candidates in (i) AI-enhanced multiscale materials modelling and (ii) autonomous materials synthesis