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additive manufactured filters as counter-measures to the formation of oxide stringers in the liquid metal. The PhD candidate, who will study at the University of Birmingham and the University and Rolls
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should be implemented via FE simulation code User Functions by the PhD candidate. The PhD project, based at Rolls-Royce and the University of Birmingham's joint High Temperature Research Centre (HTRC) will
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opportunities. This post will be funded by the $6.4M Wellcome Leap programme awarded to the University of Birmingham to study Dynamic Resilience. The purpose of the new role is to lead Wellcome Leap WP 1c and
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of plastic deformation across different planar orientations based upon the fundamental crystallographic structure of Ni-base superalloy. Thus, this PhD, based at the University of Birmingham, will aim
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modelling tools and machine learning methods. The project brings together world-leading experts in both academia and industry, across fields including superalloy metallurgy, microstructure characterisation
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at the University of Bristol and the University of Birmingham. Based at the University of Bristol, this research post will focus on developing a suite of configurable machine learning models suitable
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; Xi'an Jiaotong - Liverpool University | Southampton, England | United Kingdom | about 22 hours ago
Supervisory Team: Dr Han Wu PhD Supervisor: Han Wu Project description: In the wake of growing data privacy concerns and the enactment of the GDPR, Federated Learning (FL) has emerged as a leading
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; Midlands Graduate School Doctoral Training Partnership | Nottingham, England | United Kingdom | about 18 hours ago
ESRC DTP Strategic Joint Studentship University of Nottingham and University of Birmingham The Midlands Graduate School is an accredited Economic and Social Research Council (ESRC) Doctoral Training
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for Medium Range Weather Forecasting (NCMRWF, India). The position is within the project ‘HEavy Precipitation forecast Post-processing over India with Machine Learning’ (HEPPI-ML), which is funded through
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develop, apply and validate AI-based models (based on machine learning, agent-based, mixed-integer programming, etc) primarily to: predict energy demand in multi-energy systems (electricity, heat