Postdoctoral Researcher - Statistical Learning & Modeling

National Laboratory of the Rockies; Golden (CO); On-site; USD 77,000 - 126,000; Full time

Benefits offered by this job

Medical insurance

Pension benefits

403(b) plan

Paid time off

Relocation assistance

Job summary

National Laboratory of the Rockies in Golden, CO invites a Postdoctoral Researcher to pursue cross‑disciplinary work in statistical learning and modeling, focusing on combining statistics and deep learning to analyze energy systems data.

You will develop methods, assess disruptive events affecting infrastructures like power grids, and contribute to software for statistical and deep learning analyses, with opportunities to present at conferences and publish.

Qualifications

• Ph.D. in Statistics, Applied Mathematics or Data Science.
• Demonstrated experience with developing statistical methods, including theoretical foundations, modeling, and computational aspects.
• Demonstrated experience with dimension reduction and uncertainty quantification.
• Demonstrated experience with using deep learning software e.g. PyTorch.
• Demonstrated experience with handling scientific datasets such as computer model simulations or observational data.
• Excellent verbal and written scientific communication skills.
• Experience working with interdisciplinary teams.
• Programming experience (Python, R) and version control software.

Responsibilities

• Develop statistical and machine learning techniques and associated software.
• Characterize, model, and fuse multiple sources of information.
• Evaluate results and communicate through reports and presentations.
• Draft and publish technical reports, conference papers, and journal publications.

Skills

Statistical methods

Deep learning

Python

R

Data handling

Version control

Interdisciplinary teamwork

Communication

Education

Ph.D. in Statistics, Applied Mathematics or Data Science

Tools

PyTorch

Job description

National Laboratory of the Rockies in Golden, CO invites a Postdoctoral Researcher to pursue cross‑disciplinary work in statistical learning and modeling, focusing on combining statistics and deep learning to analyze energy systems data.

You will develop methods, assess disruptive events affecting infrastructures like power grids, and contribute to software for statistical and deep learning analyses, with opportunities to present at conferences and publish.