at Pacific Northwest National Laboratory in Springfield, Illinois, United States
Job Description
Overview
PNNL’s Earth System Science Division enables energy independence and national security through leadership in earth systems science, engineering, and decision analytics. Our work focuses on solving complex problems in the dynamic Earth system. Our interdisciplinary scientists steward a breadth of efforts that encompass research on plants to groundwater science and coastal zones, to storm prediction.
Our research focuses on understanding and mitigating operational risks at the interface of human and natural environments. This includes predicting the impacts of natural hazards and extreme climate events on Earth and human systems, along with the impacts of wildfire, flooding, sea level rise and storm surges. We focus on understanding and mitigating environmental contamination and increasing the resiliency, security and sustainability of water resources. We provide geointelligence through advanced sensing and data analytics to forecast complex system behaviors and operational performance to understand human-natural systems. This includes informed decision making and enhanced community resilience, advanced monitoring, and remote sensing of environmental systems for energy and national security. It also includes developing energy systems, including geothermal energy, sustainable oil and gas production, storage and utilization, along with carbon sequestration.
Driven by a “science-to-solutions” philosophy, we provide scientific leadership and technology to enhance national security, mitigate natural hazards and optimize disaster response. In the critical areas of energy, environment, intelligence, and defense, we deliver insights and decision support through the development of tools and solutions.
Responsibilities
DOE’s Office of Environmental Management Graduate Fellowship Program is seeking graduate fellows to work on some of the nation’s greatest cleanup efforts. Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to collaboration and work-life balance. Every year, scores of dynamic, driven interns come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!
The research associate will be responsible for the development and implementation of AI and deep learning techniques for processing and interpreting geophysical and/or hyperspectral data. The role entails designing real-time solutions for the inversion and classification of geophysical/hyperspectral data to significantly cut down computational times and improve decision-making processes. The associate will utilize advanced deep learning architectures such as Convolutional Neural Networks (CNNs), Generative Adversarial Networks (GANs), Autoencoders, and Conditional Variational Autoencoders (CVAEs) to develop algorithms for the instantaneous analysis and visualization of subsurface/surface properties. The position covers the full spectrum of algorithm development, from conceptualization and simulation to practical application and validation with real-world data. Collaboration with internal teams and external partners to integrate and refine multiple types of data for enhanced model accuracy and prediction capabilities is also key.
The successful candidate will join other graduate fellows as part of the Minority Serving Institutions Partnership Program (MSIPP). MSIPP is funded by the Department of Energy Office of Environmental Management (DOE-EM). DOE-EM is working to cleanup legacy radioactive waste found in soil, groundwater, and underground storage tanks. All research aligns with DOE-EM’s mission to safely immobilize and cleanup environmental legacy waste, focusing on cleanup of the Hanford Site which is one of the most complex DOE sites due to hazardous comingled contaminates. For more information, go to https://www.pnnl.gov/environmental-management-internship
If you are ready to test your talents and training in solving the underlying fundamental chemistry in nuclear tank waste, we want to connect with you. We encourage all qualified applicants to apply.
The successful candidate will join other graduate fellows as part of the Minority Serving Institutions Partnership Program (MSIPP). MSIPP is funded by the Department of Energy Office of Environmental Management (DOE-EM). DOE-EM is working to cleanup legacy radioactive waste found in soil, groundwater, and underground storage tanks. All research aligns with DOE-EM’s mission to safely immobilize and cleanup environmental legacy waste, focusing on cleanup of the Hanford Site which is one of the most complex DOE sites due to hazardous comingled contaminates. For more information, go to https://www.pnnl.gov/environmental-management-internship .
Qualifications
Minimum Qualifications:
+ Candidates must have received a Master’s degree within the past 24 months or within the next 8 months from an accredited college or university. Minimum overall GPA of 3.0 required.
Preferred Qualifications:
+ Master’s degree in Geophysics, Physics, Applied Mathematics, Computational Science, or a related field.
+ Experience with geophysical data modeling and inversion techniques.
+ Proficient in numerical methods, machine learning, deep learning, and programming, particularly in Python.
+ Experienced in using deep learning frameworks such as TensorFlow, PyTorch, and/or JAX.
+ Familiar with deep learning architectures like CNNs, GANs, Autoencoders, and CVAEs.
+ Skilled in software development practices, including distributed version control and continuous integration.
+ Demonstrated contributions to scientific publications and presentations at professional conferences.
+ Candidate must have graduated from a minority serving institution (MSI).
Hazardous Working Conditions/Environment
Not Applicable.
Additional Information
This position requires the ability to obtain and maintain a federal security clearance.
+ U.S. Citizenship Required
+ Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
+ Drug Testing: All Security Clearance positions are Testing Designated Positions, which means that the candidate selected is subject to pre-employment and random drug testing. In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).
Note: Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy until non-use of illegal drugs, including marijuana, for 12 months can be demonstrated.
Testing Designated Position
This position is a Testing Designated Position (TDP). The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.
About PNNL
Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!
At PNNL, you will find an exciting research environment and excellent benefits including health insurance, flexible work schedules and telework options. PNNL is located in eastern Washington State-the dry side of Washington
