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Queen’s Communities and Place (QCAP) is an AHSS Faculty flagship research initiative based in the School of Social Sciences, Education and Social Work. It launched in November 2021 and supports
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postdoctoral associate level researcher interested and experienced in applied data science to work jointly with chemists, mathematicians, and computer scientists at NIST to participate in the characterization
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Degree in Computer Science or Electrical Engineering from reputed universities, with at least 5 years research experience in related fields. Research and Comprehensive Skills: Independent and self
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Degree in Computer Science or Electrical Engineering from reputed universities, with at least 5-year research experience in related fields. Research and Comprehensive Skills: Independent and self-motivated
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metallic components (ferrous and non ferrous). Job Requirements: PhD (or Engineer with minimum 2 years of experience) in materials/mechanical engineering, in the field of solid state material recycling
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and postgraduate students. The School is also responsible for the supervision of ~120 PhD students, reflecting research strengths and expertise in the disciplines of Animal Biology, Computational
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The role This an exciting new role dedicated to supporting digital and computing innovation in the South Yorkshire region. Working with the wide range of expertise in the School of Computing and
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with strong analytical and numerical skills, and backgrounds in physics, theoretical neuroscience, applied mathematics, computer science, engineering, or related fields. Experience in relevant research
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Department of Land Surveying and Geo-Informatics Postdoctoral Fellow (three posts) (Ref. 250625011) [Appointment period: twelve to thirty-six months] Duties The appointees will assist the project
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Position as PhD Research Fellow in Machine Learning and Distributed Data Processing is available at the Department of Informatics, University of Oslo. Starting date preferably no later than 17.11.2025