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Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor
Posting Details Position Information Job Title Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor Position Number 937330 Vacancy Open to All
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Professor (25260446) Responsibilities: The Department is recruiting one scholar at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics
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from Science Faculty Niche Research Area to establish world-class research teams to develop the necessary experimental platforms, modelling and data analysis capabilities. Research Assistant Professor
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research teams to develop the necessary experimental platforms, modelling and data analysis capabilities. Research Assistant Professor (25260475) Responsibilities: The Department is recruiting a scholar at
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world-class research in spatial information science and system and provide state-of-art research training to post-doctoral fellows, Ph.D. and Master students in the field. For more information about the
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to Applicants: For full consideration, applicants must apply for the Research Assistant Professor at https://jobs.gmu.edu/. Complete and submit the online application to include three professional references
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presentations and draft sections of research papers Location: Department of Economics, Harvard University, Cambridge, MA Supervisor: Professor Gita Gopinath, website: https://gopinath.scholars.harvard.edu
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, inclusivity, diversity and transparency Where to apply Website https://www.timeshighereducation.com/unijobs/listing/406462/research-assistant-… Requirements Additional Information Work Location(s) Number
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to prepare project reports and co-author research papers. The ideal candidate is expected to be working towards a PhD in Computer Engineering, Computer Science, Computer Systems Engineering, Electronic
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at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics. Candidates with a strong background in the development of novel models and original