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longitudinal within-person models, discrete-time survival analysis, and/or explainable machine learning. Each of the three work packages is designed to result in one publication, together constituting a
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electric machines for future defence and aerospace propulsion systems. The research will explore innovative machine topologies and advanced multi-physics design methodologies to enable electric machines with
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oceans. The PhD student will be supervised by Dr Drage, and will closely collaborate with several international colleagues, primarily Prof. Minter (University of Portsmouth, UK) and Dr Pates (UCL, UK). The
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices
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The Data Management and Biometrics (DMB) group at the University of Twente is seeking one PhD candidate to join the research team of Dr. Nicola Strisciuglio to work on compositional learning
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check the minimum entry requirements for the PhD . Applicants must also satisfy Monash’s English Language Proficiency requirements; Demonstrate knowledge of machine learning, medical image analysis
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PhD Scholarship in University Students’ Learning Via Digital Twins of Neutron Scattering Instruments
Are you passionate about how to train university students for neutron-based investigation at the European Spallation Source (ESS) in Lund? Do you want to research how students learn via digital
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/machine learning tools and basic programming is a plus As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe that diversity in all its
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systems and control, applied mathematics, engineering, or a related field A strong background or interest in systems and control, applied mathematics, machine learning, and affinity with biological systems
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application