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difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
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neurosymbolic AI to extract information from unstructured text. Use NLP methods for modelling narrative text. The focus on each of these tasks can vary based on the expertise of the applicant. The University
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for the participation in multiple international conferences and interaction on site with project partners. Your qualities The ideal candidate: holds a PhD in a topic related to energy science, geoinformatics
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, while working in an ambitious, motivated, and multi-disciplinary team of veterinarians, clinicians, material scientists, biologists, and engineers. You will also participate in the co-supervision of PhD
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Vacancies Academic staff Support staff UT Student Jobs UT as employer UT as employer Employment conditions Career and development Pre and onboarding HR Excellence in Research Tenure Track PhD EngD
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, deliverable documents, and present your project updates during internal consortium meetings and external review meetings. You will also represent your work package within the consortium, not only in formal
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assessment. You will be provided with access to various engineering and computation toolsets along with the high-performance computer. A good background in numerical methods and computational platforms is
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discipline will include: becoming familiar with PA/QA practices, methodologies and disciplines (PA/QA, RAMS (reliability, availability, maintainability and safety), software PA, EEE components, and materials
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-targeted properties. This includes development of polymerization methods, formulation of coatings and their testing. In additional to the academic advisor, the PD candidate will be in close collaboration
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. You will be part of the Mathematics of Imaging & AI chair , which has ample expertise in the development of reliable and robust deep learning methods with clinical impact. The project is highly