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generative AI models to establish structure-property relationships for materials discovery. This individual will be expected to collaborate closely with the project team and coordinate efforts with
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techniques, such as neural motion models and physics-based simulation, enable the creation of lifelike animations with reduced manual intervention, benefiting industries like gaming, film, and virtual
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We seek a highly motivated Research Fellow to reverse engineer microstructured composite materials with novel
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modeling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative
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materials to enhance the cell robustness. Work plan The work plan for the PhD thesis will be divided in three main steps: 1) A chemo-mechanical model will be built to predict the crack initiation and
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monitoring. The visiting scholar intern will contribute to developing AI-enabled systems for plant health assessment, disease detection, and automated material handling. Major duties include: Design and
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financial goals through enrollment data analysis, predictive modeling, and decision support. This role combines deep analytical expertise with business acumen to transform complex data into actionable
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of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, to commence on 01.04.26. Information on the department can be found at: https://bmi.ku.dk/english/about_department
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of Position Student Position Time Status Full-Time Required Education Ph.D. in Biomedical Engineering, Materials Science or closely related field. Required Related Experience • Applicants must have extensive
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and