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for doctoral students. Overview This PhD project focuses on developing real-world deployable Machine Learning (ML) solutions integrated into Industrial Internet of Things (IoT) edge devices for condition
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Support Grant of up to £5,000 Access to Disabled Student Allowance, paid sick leave and paid parental leave Supervisor: University of Warwick: Dr Arnab Palit, Prof Andy Metcalfe Eligibility: Satisfy UKRI's
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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Research Studentship in ‘Deformation and fracture of TRISO fuel particles’ 3.5-year DPhil studentship Supervisor: Prof Dong Liu, Prof Emilio Martinez-Paneda About the Project The proposed PhD
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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learning. Supervisor: Prof. Udo Bach, Department of Chemical and Biological Engineering. (Email: udo.bach@monash.edu ) Manipulating light at the nanoscale Supervisor: Dr Alison Funston, School of Chemistry
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, at the University of Cambridge, UK. The Postdoc will work together with a team of students and research collaborators on the development of learning-based discovery of robot task/environment designs
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group at University of Luxembourg, led by Prof. Jan Lagerwall (project coordinator), the Soft and Biofunctional Materials group at NOVA University Lisbon, Portugal, led by Prof. Maria Helena Godinho, and
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure