Machine Learning for the Physical Sciences

Are you a researcher or student in the physical sciences looking to apply machine learning to your work? This session will present a series of such case studies from researchers in the fields of astrophysics, chemistry, structural engineering, earth sciences, and more.

Meet the Facilitators

Christian Jespersen, Graduate Student, Astrophysical Sciences
Rafael Pastrana, Graduate Student, Architecture
Quinn Gallagher, Graduate Student, Chemical & Biological Engineering
Holly Johnson, Graduate Student, Electrical & Computer Engineering

Preparation

If you are new to machine learning then consider attending the following two workshops as preparation:

Introduction to Machine Learning for Humanists and Social Scientists (Parts 1 & 2) by Prof. Sarah-Jane Leslie on January 13 and 14
A Hands-On Introduction to Machine Learning (Parts 1, 2, 3 & 4) by Julian Gold and Gage DeZoort on January 15, 16, 17, 21

More Training Workshops

See the entire PICSciE/RC Wintersession 2025 training program.

Accommodation

To request accommodations for this event, please contact the workshop or event facilitator at least 3 working days prior to the event.

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Co-hosted with: PICSciE/Research Computing

Contact the organizers