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-polymers using AI-driven process intensification, safe-and-sustainable-by-design principles, and smart polymer formulation. The project brings together leading academic and industrial partners to create a
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and physical synthesis techniques, along with advanced structural characterization tools, will be employed to achieve this goal. Your primary responsibilities will include: Synthesizing electrocatalysts
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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processes (e.g., application content, assessments committees’ refiguration and process) and 2) the outcome of evaluation and selection for diverse participants. The research will leverage artificial
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the monomers are reversible, making these polymer materials adaptive, healable, easy to process and recyclable. In this project, you will explore new types of stimuli-responsive supramolecular polymers
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bioinformatics, AI and ML software tools to integrate and process the datasets quickly and efficiently. You will also work closely with other computational and experimental biologists to uncover new insights
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equivalent to a two-year master's degree. Your academic background needs to be relevant to the above-stated project objectives, e.g., civil engineering, mechanical engineering, physics, or applied mathematics
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have: good knowledge of quantum mechanics knowledge of electromagnetism and solid-state physics experience with scientific programming with e.g. Python, Matlab, Julia experience with writing a scientific
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system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models and machine
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27 Aug 2025 Job Information Organisation/Company Technical University Of Denmark Department DTU Electro Research Field Engineering Physics Technology » Nanotechnology Researcher Profile First Stage