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to validate the tools against practical design requirements. The successful Machine Learning Engineer will have the following skills, experience and attributes: MSc/MEng or PhD (desirable) in Machine Learning
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Join us in designing stable materials for sustainable energy devices with machine-learning-accelerated simulation and modeling. Work assignments The postdoctoral researcher will develop machine
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Physics or an adjacent field, such as Mathematics, completed by the start of the appointment Knowledge of High Energy Theory and Machine Learning, as usually acquired through a PhD in Physics or a related
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experimental optimization, structure–performance analysis, and/or mechanistic investigations. Familiarity with machine learning techniques, optimization algorithms, and data-driven approaches for materials
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uncertainty be modelled and propagated to support large-scale change analysis? Approach: You will combine advanced robotic localisation and high-resolution mapping methods with advanced machine learning feature
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to begin August 2027. We seek excellent candidates in all areas, with specific needs in AI/machine learning, AI security, and computer systems support for AI. A demonstrated ability to collaborate with
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uncertainty be modelled and propagated to support large-scale change analysis? Approach: You will combine advanced robotic localisation and high-resolution mapping methods with advanced machine learning feature
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quantitative field. Good scientific programming skills, particularly in Python, are required. Experience with atmospheric dynamics, numerical modelling, machine learning, or large meteorological datasets would
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be responsible for designing and implementing physics-informed machine learning strategies for identifying constitutive laws in granular media. This includes the development of thermodynamically
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-temporal-resolution bulk measurements (XAS, Raman spectroscopy, XRD), with particular emphasis on pair distribution function (PDF) analysis. Machine learning approaches will be used to support these analyses