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to these challenges, working with high performance and distributed computing environments, working with large-scale machine learning models, and a proven research record of scholarly contributions through publications
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» Computer engineering Technology » Computer technology Technology » Future technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country United Kingdom Application Deadline 28 Mar
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models combining machine learning, and physics-of-failure (PoF) approaches using in-situ data • You work on projects independently • You will present your work at international conferences and
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Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
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Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
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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
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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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10 Mar 2025 Job Information Organisation/Company Instituto Politécnico de Setúbal Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions PhD