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candidate will be at the forefront of integrating advanced optical technologies with machine learning techniques to develop novel, high-performance fibre-optic sensing applications. You will be responsible
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desirable with a willingness to learn new skills. The post holder will be required to work independently and as part of a team and be computer literate with excellent communication skills. This is an
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the next generation of gas turbine engines. Successful candidates will have a PhD or equivalent in a relevant discipline and experience in the development of machine/deep learning (ML/DL) methods
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developing machine learning or data science approaches for patient stratification and genetic association analyses using cardiac magnetic resonance imaging in biobank populations. Successful applicants will
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environment. In this role, you will lead the computational strand of the project, applying molecular simulations, data analysis, and machine learning to uncover how molecular structure, charge, and surface
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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implementing the Grade 11 module of ICCS, examining civic learning among older adolescents, particularly in vocational education pathways. You will engage in international comparative research, applying advanced
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expertise in a supportive and innovative environment. In this role, you will lead the computational strand of the project, applying molecular simulations, data analysis, and machine learning to uncover how
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researchers on 5G testbed operation, integration and performance testing. Job Requirements Bachelor’s, master's or Ph.D. in Electrical and Computer Engineering, Computer Science or related field. Solid
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical technology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess