Hydrology & Water Resources Engineer (Postdoc)

Pacific Northwest National Laboratory; Richmond (VA); On-site; USD 69,000 - 119,000; Full time

Benefits offered by this job

Health insurance

Pension plan

401(k) with company match

Tuition assistance

Relocation

Job summary

Pacific Northwest National Laboratory (PNNL) seeks a PhD-level hydrology researcher to advance water resources planning and energy-related challenges. You will apply advanced data analytics, machine learning, and modeling within a collaborative, multi-project setting.

The role emphasizes rigorous publication, presenting findings, and contributing to national security and energy resiliency efforts. Strong communication and teamwork are essential.

Qualifications

• PhD in Civil Engineering, Hydrology, Geography, Environmental Science, or related technical field, received within the past five years (60 months) or expected within the next 8 months from an accredited college or university.
• Hands-on experience using a programming language (e.g., Python, R, Matlab, or C++) to analyze scientific or model datasets.
• Experience using software packages for hydraulic and/or hydrologic modeling.

Responsibilities

• Apply domain expertise in hydrology and water resources planning and management to solve complex water and energy related challenges.
• Apply advanced physical, statistical, and machine learning approaches using both commercial-off-the-shelf and custom developed tools.
• Develop technical documents for publication including presentations, reports, and peer-reviewed publications.
• Participate as an active team member on multiple projects.

Skills

Hydrology

Data analysis

Machine learning

Python

R

Education

PhD in Civil Engineering/Hydrology/Geography/Environmental Science

Tools

Python

R

MATLAB

C++

Hydraulic modeling software

Job description

Pacific Northwest National Laboratory (PNNL) seeks a PhD-level hydrology researcher to advance water resources planning and energy-related challenges. You will apply advanced data analytics, machine learning, and modeling within a collaborative, multi-project setting.

The role emphasizes rigorous publication, presenting findings, and contributing to national security and energy resiliency efforts. Strong communication and teamwork are essential.