15 learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NIST" Fellowship positions in Hong Kong
Sort by
Refine Your Search
-
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
-
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
-
) (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
-
learning models and are familiar with foundation models. Applicants are invited to contact Dr Ren Ge Gary at telephone number 3400 8595 or via email at [email protected] for further information
-
- “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
-
– “A human-like progressive learning paradigm for embodied AI: Meta skills for robots by watching and imagination”. They will be required to: (a) identify irreducible low-level sensorimotor units
-
the project leader in the research project - “Empowering language education in the AI era: Developing students’ self-regulated learning skills in English speaking”. He/She will be required to: (a) conduct
-
limited to: “Data Analytics for Social Research”, “Applied Analytical Statistics for Social Scientists”, “Machine Learning with Social Data” and “Social Networks Analysis”. The appointee should be prepared
-
-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
-
of environmental factors of 60,000 subjects across multiple time points. Our research laboratory has great computing capacity, including multiple H100 and A100 GPU systems for deep learning, and computing clusters