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Field
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• Familiarity with mechanical testing of composites • Familiarity with failure analysis of composites • 1-2 years post-doctoral experience in composites Req ID: 33110 Apply now
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Entrepreneurial culture celebrates failure as a teacher: founders share their fiascos on stage, post-mortems circulate as cautionary tales, and "fail fast" has become a mantra. Research, too, increasingly samples
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power systems, network analysis and power flow; - Experience or academic background in machine learning, Graph Neural Networks (GNN)/Grid Foundation Models and/or probabilistic methods and Monte Carlo
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include analysing material structures at the atomic level, conducting failure analysis, selecting materials for new products, and optimizing manufacturing processes Responsibilities R&D: Lead material
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, relevant experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, proof of previous data
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for Dental Crowns: From Oral Tribology to 4D Micro-CT Failure Analysis”. The laboratory-based project combines dental biomaterials, development of wear-testing methods, mechanical characterisation and advanced
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the associated levels of assurance, verification and acceptance criteria; developing hazard analysis methodologies tailored to AI-based systems, extending traditional approaches, such as FMEA and FTA, to address
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and quantitative image analysis. The results will be integrated with previous data, contributing to the characterization of the mechanisms underlying mitochondria–lysosome communication and to
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expensive and dangerous health threats, and responds when these arise. Research Project: You will gain training and experience in the analysis of large population-based and healthcare databases within
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with microfossil analysis Experience with coring and core analysis, including XRF, MSCL, imaging, grain size, and core description Experience or interest in communicating scientific results