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experimental plans. Ability to design and implement new experimental methods. High-level expertise in the required experiment or modelling methods. Ability to initiate collaboration research in multidisciplinary
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, metal-organic frameworks, and perovskitoid microstructures. Develop materials platforms for long-persistent luminescence and NIR-II emission applications, with potential use in information photonics and
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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manufacturing Definition of appropriate material stacks, materials and processes products from chemical and mechanical aspects Chemical characterization of materials within component specifications Chemical
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characterization using techniques such as XRD, SEM-EDS, and related in-house or collaborative methods. Analyze structure–property relationships and contribute to feedback loops that guide AI-based predictive models
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Development of new multidomain simulation platform for electric motor drives Development of new fabrication methods for electric motor drives Experimental testing for motor system Job Requirements: PhD degree
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devices via micro-Raman, SEM/TEM, electrical probing, and spectroscopic methods. Contribute to the validation and calibration of multimodal sensing techniques in collaboration with materials and data
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scientific industry. Demonstrated ability to formulate hypothesis and design effective experimental plans. Ability to design and implement new experimental methods. High-level expertise in the required
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experimental plans. Ability to design and implement new experimental methods. High-level expertise in the required experiment or modelling methods. Ability to initiate collaboration research in multidisciplinary
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are seeking a Research Fellow in the fields of Scientific Computing for interdisciplinary applications, to contribute to a project focused on developing and analyzing efficient computational methods for PDEs in