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of the global entertainment business and operational models Talent, brand, and artiste management in the creative sector Creative entrepreneurship, design thinking, and business innovation Planning, marketing
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twelve months] Duties The appointees will assist the project leader in the research project - “A vision-based human digital twin modelling and scene understanding approach for adaptive and natural task
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twelve months] Duties The appointees will assist the project leader in the research project - “Develop a vision-language model-based smart driving assistant for enhancing safety and convenience
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, applicants should have a Master’s degree or a good honours degree with three or more years of research/relevant work experience in the fields of operations management modelling, e-commerce logistics and ESG
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partners. Programme enhancement Align internship initiatives with curriculum objectives, design assessment frameworks, and develop scalable models for long-term development. Requirements A Master’s degree or
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Systems; Data Analytics & Technologies; Data Privacy; Digital Forensics; FinTech; Generative AI; Large Language Models; Theoretical Computer Science; Quantum Computing. The appointees will be expected
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methodologies for biological and biomedical discovery • Advanced computational approaches for large-scale multi‑omics data, biological imaging, and systems biology • Predictive modelling and data-driven
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
linear regression, mediation analysis, multilevel modeling, and/or latent variable models. Experience in managing and analyzing large datasets and in using generative AI tools for research purposes is a
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observation data analysis, physically based modelling, ecological and carbon cycle research, public health research, or environmental monitoring systems will be considered an advantage. Terms of Appointment
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supervision. Candidates with 2-3 years of postdoctoral experience are preferred. Experience with AI-driven Earth observation data analysis, physically based modelling, ecological and carbon cycle research