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of creating robust radio frequency fingerprinting (RFF) systems using machine learning. The successful candidate will have significant experience in signal processing or machine learning, and an outstanding
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fingerprinting (RFF) systems using machine learning. The successful candidate will have significant experience in signal processing or machine learning, and an outstanding track record in conducting research. You
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staff to supervise research and teaching, 51 fixed term staff and postdocs, 97 postgraduate students and 2,288 equivalent full-time student-load undergraduate students. To learn more about the School
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XRD, and the analysis of complex materials datasets · proficiency in quantitative analysis, computational methods and programming, with experience in AI, machine learning or data-driven materials
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advances in machine learning and real-time control fabricate robust instrumentation or photonic components for use at 8m-class and future ELT-class observatories perform lead roles instrument development
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: experience working with spatial omics or spatially resolved data in tissue experience applying AI or machine learning methods to digital pathology or histology data experience analysing kidney or transplant
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and/or instrument control code, leveraging advances in machine learning and real-time control fabricate robust instrumentation or photonic components for use at 8m-class and future ELT-class
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Full time, fixed term for 2 years with the possibility of extension Join the School of Electrical and Computer Engineering and contribute to pioneering research redefining CubeSat technology Base
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Infrastructure? No Offer Description Full time, fixed term for 2 years with the possibility of extension Join the School of Electrical and Computer Engineering and contribute to pioneering research redefining
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professional audiences strong planning and organisational skills with the ability to manage competing priorities proficiency in computer applications and research-related systems. Sponsorship / work rights for