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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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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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Infectious Diseases (EID) aims to pioneer the development and discovery of new and more effective methods for the treatment, prevention and control of new and emerging pathogens. The key outcome of
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are seeking a Research Fellow to contribute to a project focused on Numerical Methods for McKean-Vlasov PDEs. Key Responsibilities: Develop Numerical Methods for McKean-Vlasov PDEs/Master equations Job
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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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using, or developing, the appropriate methods and/or techniques; Lead and promote activities designed to develop collaborative research with research colleagues and support staff internally and to
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, TensorFlow, or PyTorch Familiarity with in vivo imaging, optogenetics or spatial transcriptomics methods is a plus Strong interest in bridging biological questions with quantitative approaches Excellent
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electrolysers or related fields. • Experience with large-scale electrochemical systems, including component selection, system integration, and process scale-up is highly desirable. • Proficiency in
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diffusion models using path integral formulations. This project aims to advance quantum machine learning by: Designing a quantum counterpart of diffusion models; Leveraging path integral methods to model