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- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
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- Beijing Normal-Hong Kong Baptist University (BNBU)
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Field
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areas: Statistics, Applied Mathematics Econometrics, Data Science, etc. Job Requirement Candidates should have a PhD degree in a related discipline. Successful candidates are expected to be committed
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, Operations Research, Applied Mathematics, Data Science, Financial Derivatives, Risk Management in Finance, International Finance, Fixed Income Securities. Job Requirement Candidates should have earned PhD in
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mathematics modules at all levels, as well as the PhD programme. Research interests in the Department of Physics currently include particle physics, condensed matter physics and materials science, dynamical
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well as the PhD programme. Research interests in the Department of Physics currently include particle physics, condensed matter physics and materials science, dynamical systems, theoretical physics, and
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Finance, FinTech. Job Requirement Candidates should have a PhD degree in a related discipline. Successful candidates are expected to be committed to excellence in undergraduate or postgraduate teaching
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should have a PhD degree in a related discipline. Successful candidates are expected to be committed to excellence in teaching at undergraduate or postgraduate levels. Preference will be given
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theater and drama studies. Job Requirement Candidates should have a PhD degree in a related discipline. Successful candidates are required to demonstrate promise and/or substantial production as a scholar
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Communication, etc. Job Requirement Candidates should have a PhD degree in a related discipline. Successful candidates are expected to be committed to excellence in teaching at undergraduate or postgraduate
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Candidates should have a PhD degree in a related discipline and a strong sense of responsibility and professional ethics. Extensive industry experience will also be considered. Successful candidates
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optimization algorithms for both estimation and inference. Special emphasis is placed on advancing statistical approaches to address the demands of increasingly complex, high-dimensional, and unconventional data