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structures, followed by thorough characterization of their chemical, structural, and mechanical properties. You will work on understanding and optimizing foam properties such as porosity, elasticity, and
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solvers and optimization algorithms for 1 year and 4 months. The Section of Solid Mechanics conducts research and teaching in the fields of structural and materials mechanics, vibration and their active
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: Utilize Python, R, SQL, and containerization (Docker, Kubernetes) to run data ingestion and processing within automated data pipelines Optimize data processing workflows, reducing manual intervention
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partners and optimize them for nonlinear quantum processes Collaborate with theory colleagues to refine fiber designs based on experimental feedback Disseminate results at international conferences and in
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skills and a keen interest in data-driven research. Your role will be to apply the developed semantic infrastructure to concrete case studies—such as cross-unit scheduling, process optimization
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the ambitions to accelerate the detection and optimization of sustainable chemical approaches through the development of novel reactions and advanced analytics using state of the art high-field and hyperpolarized
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optimization, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured
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coating production and coating use. Test methods Reliable and fast test methods to optimize coating performance is of utmost importance in coatings development. We work on new test methods and optimisation
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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
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Method to analyze the single-photon source performance (PhD1). Optimize and propose new single-photon source designs overcoming these limitations to be fabricated by other PhD students (PhD1). Perform