21 machine-learning-"https:"-"https:"-"https:" Fellowship positions at Hong Kong Polytechnic University
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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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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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- “Reliable industrial foundation models for trustworthy industrial robot fault diagnosis in automotive smart manufacturing”. He/She will be required to: (a) carry out research in advanced machine learning
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-science and signal-analysis tasks, including processing experimental signals, integrating datasets, developing machine-learning models, and mapping measured fuel properties to SAF performance. For the post
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analysis and application of machine learning techniques to structured numerical and unstructured textual data; (d) have a good track record of academic writing, including report writing, manuscript
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State Key Laboratory of Ultra-Precision Machining Technology Postdoctoral Fellow / Research Associate / Research Assistant / Part-time Research Assistant (Ref. 260914003) (1) Postdoctoral Fellow
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publications at major machine learning, AI or closely related conferences and journals; and (b) good communication and writing skills in English. Applicants are invited to contact Prof. Qiu Anqi via email at
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analysis, computer programming and using commercial optimisation solvers. Applicants are invited to contact Prof. Kai Pan at telephone number 2766 5545 or via email at [email protected] for further
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– “Smart ultra-precision machining for damage-free diamond wafers”. Qualifications Applicants should have a doctoral degree or an equivalent qualification and must have no more than five years of post
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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