Post Doc Research Associate - Data Science/Geophysics

Key Skills

Aartificial intelligence, Data science techniques, Deep Learning, JAX framework, Machine learning techniques, PyTorch, TensorFlow

Job Description

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

The Computational Geophysics Team, within the Subsurface Science Group, is seeking applications for a talented, highly motivated post-doctoral researcher to join its team. The postdoctoral researcher will primarily focus on the development and implementation of Artificial Intelligence (AI) and deep learning-based methods for the processing and inversion of geophysical data. This role involves creating innovative solutions to enable real-time inversion and classification of geophysical data, aiming to significantly reduce computational times and enhance decision-making in near real-time scenarios. The postdoc will work on leveraging advanced deep learning architectures, such as Convolutional Neural Networks (CNNs), Generative Adversarial Networks (GANs), Autoencoders, and Conditional Variational Autoencoders (CVAE) to develop algorithms capable of instantaneously analyzing data and producing images of subsurface properties. The candidate will engage in the full cycle of algorithm development—from theoretical inception and numerical simulation to practical implementation and validation using real-world data. This position also requires active collaboration with internal teams and external partners to integrate multiple types of geophysical data, improving the accuracy and reliability of subsurface models. Additionally, the researcher will contribute to the refinement and enhancement of these models by incorporating site-specific data, thereby improving the prediction capabilities of the system. The ultimate goal is to execute these algorithms via edge computing, enabling efficient on-site data analysis even in environments with limited connectivity.

Qualifications

Minimum Qualifications:

• Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university.

Preferred Qualifications:

• PhD in Geophysics, Physics, Applied Mathematics, Computational Science, or a related field.
• Experience in modeling and inversion of geophysical data, including electromagnetic, magnetic, gravity, seismic, and/or ground penetrating radar data.
• Proficiency in numerical methods, machine learning, deep learning, and scientific programming, including Python.
• Proficiency in deep learning libraries such as TensorFlow, PyTorch, and/or JAX.
• Working knowledge of deep learning architectures such as Convolutional Neural Networks (CNNs), Generative Adversarial Networks (GANs), Autoencoders, Conditional Variational Autoencoders (CVAE), and/or hybrid architectures.
• Experience developing or working with software that utilizes continuous integration tools (e.g., distributed version control, automated testing).
• A record of peer-reviewed publications, active engagement in professional societies, and presentations at professional conferences.

Hazardous Working Conditions/Environment

Not Applicable.

Additional Information

Not Applicable.

Testing Designated Position

Not a Testing Designated Position.

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 known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.

Commitment to Excellence, Diversity, Equity, Inclusion, and Equal Employment Opportunity

Our laboratory is committed to a diverse and inclusive work environment dedicated to solving critical challenges in fundamental sciences, national security, and energy resiliency. We are proud to be an Equal Employment Opportunity and Affirmative Action employer. In support of this commitment, we encourage people of all racial/ethnic identities, women, veterans, and individuals with disabilities to apply for employment.

Pacific Northwest National Laboratory considers all applicants for employment without regard to race, religion, color, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.

We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov.

Drug Free Workplace

PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.

If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug. If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.