This internship focuses on building connected, end-to-end datasets and workflows that enable more efficient R&D operations and decision-making.

Responsibilities:

Design and build connected datasets and repeatable data pipelines for R&D applications.
Integrate data from multiple sources and improve data-joining processes.
Develop validation methods that improve data quality, consistency, and reliability.
Create Python and SQL solutions that streamline engineering workflows and reduce manual tasks.
Apply AI and machine-learning methods to experimental data to identify patterns and generate insights.
Document technical solutions, results, and recommended process improvements.
Collaborate with engineering, software, and data stakeholders to deliver project objectives.

Education and Experience Required:

Currently pursuing a Ph.D. in Computer Science, Mechanical Engineering, Chemistry, Chemical Engineering, Data Science, or a related technical field.
Must be enrolled full-time at an accredited university.
Has no more than 24 months of prior work experience professionally related to the intern requisition they are applying to (not including internships, teaching assistance, research work, or military experience).
Able to obtain work authorization in the United States in 2027, and not require sponsorship in the future.
Experience with programming, data analysis, databases, or engineering data workflows.
Understanding of data integration, validation, and software-development principles.
Strong analytical, project-management, and technical communication skills.

Knowledge and Skills:

Electrical/Hardware Engineering Intern

Skills