Postdoc in Statistical Learning & Energy Systems Modeling

National Renewable Energy Laboratory; Golden (CO); On-site; USD 77,000 - 126,000; Full time

Job summary

The National Renewable Energy Laboratory in Golden, CO invites applications for a Postdoctoral Researcher to pursue cross-disciplinary research in statistical modeling, with emphasis on combining statistics and deep learning.

The successful candidate will develop statistical and machine learning techniques, handle large datasets and assess disruptive events impacting power grids, and contribute to reports, papers, and software.

Qualifications

• PhD in Statistics, Applied Mathematics or Data Science.
• Recent PhD graduate within the last three years.
• Experience with developing statistical methods, theory, modeling, and computational aspects.
• Experience with dimension reduction and uncertainty quantification.
• Experience using deep learning software (PyTorch).
• Experience handling scientific datasets (e.g., computer model simulations, observational data).
• Excellent verbal and written scientific communication skills.
• Experience working with interdisciplinary teams.
• Programming experience in Python and R and version control.

Responsibilities

• Develop statistical and machine learning techniques and software to characterize, model and fuse multiple information sources.
• Focus on disruptive events and their impacts on infrastructures such as power grids.
• Evaluate and communicate results through written reports and presentations, and assist in engineering and writing software.
• Draft and publish technical reports, conference papers, and journal publications.

Skills

Statistics

Python

R

Deep Learning (PyTorch)

Dimension Reduction

Uncertainty Quantification

Scientific Datasets Handling

Communication

Interdisciplinary Collaboration

Education

PhD in Statistics, Applied Mathematics or Data Science

Tools

PyTorch

Python

R

Git

Job description

The National Renewable Energy Laboratory in Golden, CO invites applications for a Postdoctoral Researcher to pursue cross-disciplinary research in statistical modeling, with emphasis on combining statistics and deep learning.

The successful candidate will develop statistical and machine learning techniques, handle large datasets and assess disruptive events impacting power grids, and contribute to reports, papers, and software.