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Job Description Job Alerts Link Apply now Job Title: Research Analyst/ Associate/ Fellow in Machine Learning and Artificial Intelligence (ML/AI) Posting Start Date: 19/09/2024 Job Description: The
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researchers from the departments of Geography and Geoinformation Science (GGS), Computational and Data Sciences (CDS) and Computer Science (CS). About the Position: The Center for Geospatial Intelligence
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of the research programme as discussed with the fellowship supervisor. Contribute to research group planning. Coordinate and liaise with other members of the research group over work progress. Supervise research
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intelligence with Bowdoin’s liberal arts mission, focusing on its societal, ethical, and humanistic dimensions.The gift will fund new faculty positions across disciplines, support faculty in AI-related teaching
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knowledge of personal computers and relevant software programs (e.g., data entry, word processing, spreadsheets, qualitative and quantitative data analysis software) such as Microsoft Word, Excel, PowerPoint
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The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and Technology (KAUST) is
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with education and experience Restricted: Yes Criminal Background Check: Yes About the Department: The Center for Spatial Information Science and Systems (CSISS) is an interdisciplinary research center
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% teaching component. The Department teaches in all the sub-fields mentioned above. The successful candidate will be part of the Faculty’s PhD programme. The work is expected to lead to a PhD in political
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are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources for end-to-end
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of the project on the “Intelligent Modelling for Decision-making in Critical Urban Systems (Descartes). Reporting directly to the Principal Investigator, the Research Assistant must facilitate key administrative