102 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at University of Birmingham
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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experience in the use and/or development of machine learned interatomic potentials would be seen as a significant asset. Previous experience of inelastic neutron scattering spectroscopy (or similar) would be
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for Robotics in the School of Engineering. The Institute brings together multidisciplinary researchers to explore all aspects of robotics, automation, autonomous systems, AI and smart machines. The studentship
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set up and take out, cleaning of the machine. Attending training once a month outside of normal shift pattern, lifeguard training, situational training, fire warden training. Dry side (including indoor and
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personalised, ethnically-stratified risk scores. This is a highly interdisciplinary project at the intersection of machine learning, health equity, and precision medicine. The successful candidate will join a
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. Clinical service as part of an honorary contract with the Birmingham Community Health Care Foundation Trust. Main Duties Education You will contribute across the range of teaching and learning activities
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learning activities: making a significant contribution to the pedagogical knowledge base of the subject that advances teaching through the enhancement of practice, the development of teaching resources and
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are open to adjacent areas that can interface with SERENE’s mission): AI/ML & Data-Centric Space Environment Modelling Machine learning, deep learning, Bayesian methods, or hybrid physics-ML models
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, flight dynamics and operations. Stability and control of air vehicles using novel methods and/or for innovative platforms. Application of novel machine learning approaches to practical future flight
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underpin our research and provide an exceptional learning environment. EESE delivers internationally recognised research and education across communications and sensing, electrical power systems, cyber