About Jack
Jack Muir is the Head of Machine Learning at Fleet Space technologies. His focus is on adding value to Fleet’s geophysical measurements and inversions by synthesising geophysical features with other datasets to meet client targeting and interpretation needs at the tenement scale. Jack has a background in seismology, with a PhD from Caltech on inversion and ML methods for surface wave tomography and distributed acoustic sensing. He was a Marie Sklodowska-Curie fellow at Oxford, where he studied physics informed neural networks for solving the seismic wave equation, as well as active seismic methods for environmental and agricultural seismology. Jack has a Bachelor of Philosophy (Science) with 1st Class Honours from the ANU. He was a member of the Australian Conference of Undergraduate Research, and has worked with Australian Nuclear Science and Technology Organisation (ANSTO), and the Australian Astronomical Observatory (AAO), and student science and engineering organizations.
