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Location: United Kingdom (Remote or Belfast, NI Office based) Position Overview We are seeking a Senior Machine Learning Researcher with deep expertise in computer vision and hands-on experience
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page at: https://www.ncl.ac.uk/sage/ This is a full time, fixed term role for 3-4 months. Knowledge, Skills, and Experience AI and Machine Learning Skills: proficiency in various AI and machine learning
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the Infrared sensors are working in overlapping field of view The Person (Essential) Knowledge, Skills and Experience Track record of design, deployment and evaluation of machine/deep learning-based techniques
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integrated with the NiMARE (NMA) software project. To be considered you will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain
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will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain imaging data and possess sufficient specialist knowledge in brain
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Transactions on Probabilistic Machine Learning. A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, L Kennedy, J Gabry, PC Bürkner, M Modrák (2020). Bayesian Workflow. B Carpenter, A Gelman, MD
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for candidates with exceptional skills and grades in engineering or physics and/or computer science and/or signal processing, with the strong and proven knowledge of machine learning and/or some expertise in
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the challenge of time-consuming sideshaft testing. As a key member of the team, you will apply cutting-edge machine learning and deep learning techniques to dramatically reduce testing cycles. You will lead life
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through