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statistics. Qualifications: Excellent academic background, PhD degree, undergraduate and graduate studies should be carried out at renowned universities. Capable of continuously publishing high-impact research
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. Teaching and research areas: All areas in mathematics and statistics, and cross-disciplinary research areas related to mathematics and statistics. Qualifications: Excellent academic background, PhD degree
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• University housing or housing subsidy • Light teaching load, adequate facilities, dedicated office space, and strong research support Applicants must hold a PhD and should have outstanding accomplishments in
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& Characterization; Controlling Factor and Macroscale Model of Carbon Emission; Monitoring Reporting and Verification, and Marine Carbon Dioxide Removal. Job description Requirements Applicants with a PhD in Natural
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ERDI. Essential Qualifications/Experience A PhD in Computer Science, Data Science, Artificial Intelligence, and, ideally, a PgCert HE or equivalent. Ideally, a few years of teaching/research experience
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-related tasks assigned by the Dean or Director of ERDI. Essential Qualifications/Experience A PhD in computer science, data science, artificial intelligence, and, ideally, a PgCert HE or equivalent. Ideally
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seminars on topics within the School of AI and Liberal Arts. Candidates must have a PhD in computer science, mathematics/statistics, or closely related disciplines and an international reputation in research
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of undergraduate, postgraduate, MBA, PhD and Executive Education programmes in the fields of Economics, Management, Accounting and Finance. Undergraduate programmes in Economics include both the widely
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part-time position as Chair Professor (typically 1.00.000 RMB/month). On-campus presence is required for two months per year. The applicant should bring the following qualifications: PhD in one
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quality research and innovation. Identify and implement strategies to maximise grant capture and research income from external funding bodies and business/industry. Supervise PhD students and mentor Early