Michael Craig
About Michael Craig
Michael Craig is a Machine Learning Engineer currently working at Carbon Re in London, where he applies machine learning techniques to support the decarbonisation of heavy industry. He holds a PhD in Computational Chemistry from Trinity College Dublin and has experience in both computational chemistry and theoretical physics.
Work at Carbon Re
Michael Craig has been employed as a Machine Learning Engineer at Carbon Re since 2022. In this role, he focuses on applying machine learning techniques to support the decarbonisation of heavy industry. His work contributes to the organization's mission of promoting a zero carbon future through innovative technology solutions.
Education and Expertise
Michael Craig holds a Doctor of Philosophy (PhD) in Computational Chemistry from Trinity College Dublin, where he studied from 2018 to 2022. He also earned a Bachelor of Arts in Theoretical Physics, achieving a 1.1 classification, from the same institution between 2014 and 2018. His educational background provides a strong interdisciplinary foundation, combining knowledge from computational chemistry and theoretical physics, which is essential for addressing complex challenges in machine learning.
Background
Prior to his current position, Michael worked in various roles that enhanced his expertise in data science and engineering. He served as a Data Science Intern at Corvil for two months in 2018 and as an Infrastructure Engineering Analyst at Datalex for four months in 2018. Additionally, he completed a three-month internship as an Infrastructure Engineering Analytics Intern at Datalex in 2017. His experience includes volunteering at FoodCloud, where he demonstrated a commitment to community service.
Achievements
Michael Craig has contributed to groundbreaking AI research and published an article on the role of AI in enabling materials simulation. His work at SLAC National Accelerator Laboratory as a Visiting Researcher in 2022 provided him with international research experience in a leading scientific environment. This experience, along with his academic achievements, underscores his ability to apply university knowledge to real-world challenges.