Citrine is the data platform for the physical world. Our platform ingests and analyzes vast quantities of technical data on materials, chemicals, and devices to streamline R&D, manufacturing, and supply chain operations for any organization that produces a physical product. Our users are scientists and engineers at large manufacturing and materials companies, as well as researchers at universities and government labs, and our platform is an essential workflow tool that enables these users to analyze tremendous quantities of technical data.
Data Science and Engineering Intern
In this internship, you will combine knowledge of physical science with data science and machine learning to build predictive models for various material properties. You will also visualize and communicate results for materials scientists who are often unfamiliar with machine learning concepts. Further, you will grow Citrine's vast materials database, and use machine learning and other tools to identify possibly spurious or physically unreasonable data points that would have a detrimental effect on models. Interns will present results to the Data Science, Data Operations, and executive leadership teams at Citrine.
Who should apply
Stanford undergraduates who have demonstrated excellence and conscientiousness (i.e., the ability to deliver) in their academic career to date. Candidates who believe in our mission and want to play a role in shaping the future of materials and manufacturing.
Background or strong interest in material science, physical sciences, and coding.