Responsibility: The successful candidate will join a NASA funded project working with Caltech Jet Propulsion Lab to detect wildfires from satellite date using topological data analysis (TDA) and machine learning under the direct supervision of Professor Matthew Dixon. There is a possibility that the successful candidate will also teach at the undergraduate and graduate level in the Department of Applied Mathematics in Year 2 of the appointment.

Required and Preferred Qualifications: The successful candidate should have a recent PhD in applied mathematics or related fields. Applicants specializing in machine learning and data sciences, combined with disciplined statistical and scientific programming codes as evidenced by, for example, well documented data science research codes in Github and publications, are especially encouraged to apply. Preference will be given to candidates who can start by the preferred start date of April 1st and who can demonstrate a sound theoretical background in TDA, and engineering know-how of applying machine learning and TDA for anomaly detection in multi-channel satellite image data.