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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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conceptual framework linking nanoscale features to macroscopic adsorption efficiency. Generate and curate high-quality datasets to support data-driven materials optimization and future integration with AI
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Engineering, section for Fluid Mechanics, Coastal and Maritime Engineering. The PhD project will play an integral part of the project “Marine advection and dissipation in the vegetated coastal environment
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Job Description Are you ready to launch your scientific career by addressing the urgent need of renewable energy integration? At DTU Construct you will break new ground at the absolute forefront
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developing and deploying an ocean‑monitoring system for offshore installations. The research will integrate optical and acoustic sensors, autonomous data collection, and advanced perception methods to track
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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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top interdisciplinary scientists from all over the world and make a personal impact in solving some of the most critical challenges in the built environment. The position is also integrated
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privacy guarantees. This PhD project will develop scalable, privacy-preserving coordination models that jointly optimize DER integration, electrified loads, and data-center flexibility — ensuring fairness
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by Printing and etworked Robots” (AM2PM). The goal of AM2PM is to develop and experimentally validate a complex digital infrastructure that integrates sustainable material design, computational
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that ensures integrity in our work. Therefore, we strive for and take responsibility for driving the democratisation of digital technologies, so that everyone has the opportunity to actively participate in