Fwd: [Apply] US National Lab Summer Internships at PNNL [Bachelors, Masters, PhD]
Jessica Sadler
From: Rawson, Michael <michael...@pnnl.gov>
Date: Mon, Jan 16, 2023 at 4:54 PM
Subject: [Apply] US National Lab Summer Internships at PNNL [Bachelors, Masters, PhD]
To: Jessica Marie Sadler <jsa...@umd.edu>, Radu Victor Balan <rvb...@umd.edu>
For UMD students:
US National Lab Summer Internships at PNNL:
Diverse Focus Areas: Your internship can be in one of five technical groups.
1. Math, Stats, and Data Science: We employ powerful tools and techniques, such as mathematical modeling and computational statistics, graph and game theory, network science, and uncertainty quantification to solve complex problems in a variety of domains.
Disciplines: Applied Mathematics, Machine Learning, Statistics, Operations Research
2. Applied AI Systems: We develop hardened and robust models to distill large, fast, distributed, and messy data into knowledge to support decision processes in operational environments on sponsor systems.
Disciplines: Artificial Intelligence, Applied Machine Learning, Data Science, Deep Learning, Computer Vision, Geospatial Intelligence, and Natural Language Processing
3. Foundational Data Science: We conceptualize and develop fundamentally new algorithms and tools to address unresolved challenges in distilling large, fast, distributed, and messy data into knowledge to support sponsors’ decision processes.
Disciplines: Artificial Intelligence, Applied Machine Learning, Data Science, Deep Learning, Computer Vision, Geospatial Intelligence, and Natural Language Processing
4. Software Engineering & Architectures: We develop high-quality, scalable, cloud-first solutions for tackling large data pipelines and analytics that are delivered to operational sponsor environments. We use industry best practices for professional software development using Agile development practices, code reviews, automated testing, and CI/CD pipelines.
Disciplines: Cloud Engineering, Large-Scale Data Engineering, Scalable Machine Learning/Artificial Intelligence, DevSecOps, Automated Testing, Software Engineering
5. Human Centered Computing: We combine innovative interactive visualizations with advanced automated data analysis techniques to enable users to gain deeper insights from their data. Make complex data useful through skillful visual design, compelling human computer interaction, sound analytic methods, and solid engineering.
Disciplines: Data Science, Human-Computer Interaction, User Experience, Software Engineering, Natural Language Processing, Graph Analytics and Data Visualization
Learn about the lab:
Requirements:
US Citizenship is required.
Minimum GPA of 3.3 is required.
Best,
Michael Rawson