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7th February 2025 Languages English Norsk Bokmål English English PhD Fellowship in Statistical Physics and Machine learning modelling for battery materials Apply for this job See advertisement Job
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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
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interest and competence in practical application of statistical learning or machine learning Working environment: The project will be done in an interdisciplinary team. The successful candidate will work in
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the following fields: Computer Architecture Algorithms and Optimization Health Research Human-Computer Interaction Machine Learning and ML Foundations Machine Perception Natural Language Processing (including
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/or FE simulation results and modern machine learning methods may be evaluated for this purpose. The current project is relevant for a wide range of academic and engineering disciplines, including
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create statistically significant data. Use the measurement data to improve digital models of the structure and the load process for relevant excitation, such as traffic and wind. Explore machine learning
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perspectives of our Department. Fellowship recipient responsibilities: Teach one course each in the fall and the spring semesters, which could include advanced courses in contemporary movement practices and/or
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and aerodynamic loads. The project will be co-supervised by experts in aeroelasticity and machine learning and can include aspects of fluid-structure interaction and digital twins depending
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breadth or depth of specialist and core knowledge in the discipline, demonstrated by a PhD or equivalent in Medieval History, to develop teaching programmes, and teach and support learning Use a range of
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is essential for the successful completion of this PhD project. Key Qualifications: A solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning