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Field
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networks of these devices we will use digital twins; machine learning models trained to predict physical systems but are differentiable. This project will advance the machine learning methods, particularly
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developments in machine learning (ML) for phase retrieval. This project is a collaboration with the Ada Lovelace Institute and Diamond Light Source. If you are interested, please contact the supervisor for more
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related to staff position within a Research Infrastructure? No Offer Description Overview Qualification type: PhD Subject area: Control and Machine Learning Location/Campus: College Lane, Hatfield Closing
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The Data-Driven Mechanics Laboratory is seeking a highly motivated doctoral student to study physics- and thermodynamics-informed machine learning (ML) for the mechanics of material failure
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Phenotyping” offers a position from 01.03.2024 as PhD student (m/f/x) for development and implementation of machine learning applications and data analysis in Translational Psychiatry Kennziffer: 8740. Your
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Supervisory Team: Hector Calvo-Pardo; Vahid Yazdanpanah; Tiago Alves (Solar Americas ); Enrico Gerding PhD Supervisor: Hector Calvo-Pardo Project description: Machine learning (ML) holds immense
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telemetry equipment. They will be responsible for ensuring high quality twins, and will interact with the project team on the development of effective machine-learning models to be deployed within these twin
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29th May 2024 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Interpretable Machine Learning (The LABDA Project) Apply for this job See
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interpretability and predictive accuracy. We want to explore the structural parameters in choice models (e.g., random coefficient logit models) and obtain valid inferential results using machine learning-enhanced
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well on various excellence ranking lists. FEBRI, the graduate school and research institute of the Faculty of Economics and Business has one PhD position in the field of Machine learning meets choice