Using an artificial neural-network machine learning interatomic potential, we have performed molecular dynamics simulations to study the structure and dynamics of liquid close to the Earth's liquid core conditions. The simulation results reveal that the short-range structural order (SRO) in the liquid is very strong. About 80% of the atoms are arranged in crystallinelike SRO motifs. In particular, of Fe-centered clusters can be classified as either hexagonal-close-packed-like or icosahedrallike SRO motifs. The SRO clusters centered on Fe, Si, or O atoms are strongly intermixed and homogenously distributed throughout the liquid. The atomic structure of the liquid and the fractions of dominant SRO clusters are not sensitive to pressure/temperature used in the simulations except that the SRO of the O-centered clusters is enhanced close to inner core pressures. The O-diffusion coefficient is about two to three times larger than the Fe and Si ions and increases more rapidly in the deeper core regions.