66 learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Adelaide-University" positions in Hong Kong
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Duties Provide academic and personalised support to the students under the Student-Athlete Learning Support and Admission Scheme; Plan, coordinate, and organise local and non-local student
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posts) [Appointment period: each for six months] Duties The appointees will assist the project leader in the research project - “Statistical learning and inference for 3D tensor objects with applications
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Holistic Insurance Enhancement using Learning Algorithms & Decentralization (S.H.I.E.L.D.)”. He/She will be required to: (a) develop machine learning models to predict optimal rehabilitation solutions
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honours degree or an equivalent qualification. For both posts, applicants should also have research experiences in: (1) Machine learning and DFT calculations for hybrid perovskites or other functional
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English language (native speaker of English preferred); (d) effective communication skills; and (e) proven experience in producing English language learning materials. Applicants are invited to contact Dr
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machine learning and robot navigation; and 3) the ability to publish research findings in high-impact international journals. Applicants are invited to contact Miss Samantha M. S. Sin at telephone number
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project - “Safe-assured learning-based deep SE(3) motion joint planning and control for unmanned aerial vehicles”. He/she will be required to: (a) assist in literature review, data collection, algorithm
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well as to teach existing courses in language acquisition. The appointment will be made at the rank of Professor, Associate Professor, or Assistant Professor, commensurate with the successful candidate’s
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will assist the project leader in the project - “Understanding learning difficulties”. They will be required to: (a) coordinate service-learning activities for students; (b) assist in service
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) (several posts) [Appointment period: each for one to eight month(s)] Duties The appointees will assist the project leader in the research project - “Collaborative agentic reinforcement learning and proactive