11 aerospace-composite-structures Fellowship positions at Hong Kong Polytechnic University
-
in the research project - “Towards efficient stamp forming of thermoplastic composites through data-driven thermo-mechanical modelling”. Qualifications Applicants should have a doctoral degree or an
-
from rich multimodal demonstration data; (b) conduct research on skill composition for complex long-horizon tasks; (c) develop methods for atomic skill retrieval and representation; (d) develop
-
the surface interface and structure-activity correlations in zeolites”. Qualifications Applicants should have: (a) a PhD degree in Chemistry, Chemical Engineering, Materials Science or a related discipline
-
months] Duties The appointees will assist the project leader in the research project - “Atomic structure, stability, and deformation mechanisms of ultrastrong-yet-ductile refractory high-entropy alloys
-
/ Research Assistant [Appointment period: each for twenty-four months] Duties The appointees will assist the project leader in the research project - “Study on grain structure control of high-purity oxygen
-
] Duties The appointees will assist the project leader in the research project - “Development of high-performance functionally graded materials by additive manufacturing with tailorable gradient compositions
-
Department of Construction Management and Intelligence Postdoctoral Fellow / Research Associate / Research Assistant (Ref. 260724001) (1) Postdoctoral Fellow [Appointment period: twelve months
-
project - “Adaptive interleaves for sustainable, out-of-autoclave manufacturing of high-performance CFRP structures in large aircraft”. Qualifications Applicants should have a doctoral degree in Materials
-
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
-
twelve months] Duties The appointees will assist the project leader in the research project - “Construction skill transfer learning for smooth worker-robot collaboration in dynamic and uncertain workplaces