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Patrick holds a PhD in Physics from Dalhousie University in Canada, and completed his postdoctoral research studies at Lawrence Livermore National Laboratory in California.
Patrick has over ten years of work experience programming and building sophisticated scientific models, both in academic and industry environments. In Patrick's PhD thesis he developed a scientific approach to study the surface diffusion of organic molecules, using stochastic modelling and density functional theory. His postdoctoral work focused on materials discovery for batteries and hydrogen fuel cells using large scale computational physics simulations. He worked closely with other researchers to aid in the interpretation of experimental data and provide insights into new high performance materials.
Prior to joining Chelsea Avondale, Patrick worked as a Data Science Fellow at Insight Data Science – a fellowship program backed by Y Combinator where he brought innovative solutions to startups in a consulting capacity using Python and AWS. Patrick leverages his background as a computational scientist to improve our physics-based catastrophe models. He has also worked on the development of machine learning models to significantly increase automation in parts of the policy administration system.
In addition to his PhD and postdoctoral research, Patrick holds a Masters of Science in Physics from Dalhousie University, and a Bachelor of Science degree in Physics from St. Francis Xavier University in Canada.