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.
The Coastal Sciences Division, headquartered at the Pacific Northwest National Laboratory’s Sequim Marine Research Operations on Washington State’s Olympic Peninsula, is the Department of Energy’s only marine research laboratory. This unique facility and the capabilities of its researchers deliver science and technology that is critical to the nation’s energy, environmental and security future.
Building upon a history of research related to marine and coastal resources, environmental chemistry, water resources modeling, ecotoxicology and biotechnology—and more recently, national and homeland security—the MSL is emerging as a leader in these three areas:
- Enabling sustainable development of ocean energy
- Understanding and mitigating long-term impacts of human activities, including climate change, on marine resources
- Protecting coastal environments from security threats
The Coastal Modeling Team in the Marine and Coastal Research Laboratory at the Pacific Northwest National Laboratory (PNNL) is seeking a research associate with a strong background in computer science and experience/interest in applying Machine Learning to solve earth science related problems. The successful candidate will join a small team of scientists to work on developing and improving Deep Neural Network-based models with application to tropical cyclone rainfall estimation. Domain knowledge related to tropical cyclones is not essential; however, experience and interest within earth system science will be beneficial. The candidate will also be expected to conduct data analysis on geospatial data and to assist with tropical cyclone risk analysis using the developed framework.
- Candidates must have received a Bachelor’s degree within the past 24 months or within the next 8 months from an accredited college or university
- Minimum overall GPA of 2.5 required.
- Apply knowledge of software engineering practices (e.g. source control, problem tracking, design principles, etc.) with minimal oversight
- Programming experience in Python (including NumPy, Pandas, MatPlotLib, TensorFlow or Pytorch)
- Experience in design and development of Machine Learning Models
- Experience in conducting literature review and possess excellent verbal/written communication skills
- Conduct code reviews on components and applications to ensure adherence to the development standards and best practices
- Perform unit testing and system integration testing of the newly developed functionality
- Bachelor degree in Computer Science, Computer Engineering, or related field
- Degree in Atmospheric Science, Earth Science, Oceanography, or related field may also apply
- Candidate needs to prove programming skills in at least one object-oriented programming language such as Python, Java, C#, or C++
- The candidate is expected to be enthusiastic, self-motivated to work on technical tasks on their own, as well as able to work as a part of a multidisciplinary team
- Preferred GPA of 3.5
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 email@example.com.
Battelle requires employees to have a COVID-19 vaccine as a condition of employment, subject to accommodation. Applicants are required to disclose their vaccination status following a conditional offer of employment and must attest to being fully vaccinated with a Center for Disease Control (CDC)-approved COVID-19 vaccination, or provide documentation of need for medical or religious exemption from the COVID-19 vaccination requirement.