Role overview
- Research Associates excluded.
Responsibilities
- Designs, develops, and implements methods, processes, and systems to analyze diverse data.
- Applies knowledge of statistics, machine learning, advanced mathematics, simulation, software development, and data modeling to integrate and clean data, recognize patterns, address uncertainty, pose questions, and make discoveries from structured and/or unstructured data.
- Produces solutions driven by exploratory data analysis from complex and high-dimensional datasets.
- Designs, develops, and evaluates predictive models and advanced algorithms that lead to optimal value extraction from the data.
- Demonstrates ability to transfer skills across application domains.
Basic qualifications
- BS/BA and 5+ years of relevant experience -OR-
- MS/MA and 3+ years of relevant experience -OR-
- PhD with 1+ year of relevant experience
Preferred qualifications
- PhD or MS in Robotics, Computer Science, Applied Mathematics, Electrical Engineering, Mechanical/Aerospace Engineering, or related scientific fields.
- Hands-on experience in robot learning, motion planning, navigation, and control using both classical and modern control methods (e.g., MPC, PID, LQR) and modern machine learning techniques (e.g., reinforcement learning, imitation learning, computer vision).
- Experience leading or contributing to R&D proposals for federal agencies (e.g., DOE, DARPA, NSF), with a history of successful funding as PI or co-PI.
- Deep understanding of robot kinematics, dynamics, and sensor integration and perception pipelines.
- Familiarity with multimodal perception and embodied AI for safe context-aware autonomous decision-making.
- Experience with physics-simulation frameworks such as MuJoCo, Gazebo, and IsaacSim.
- Strong programming skills in Python/Julia/C++, ROS, and machine learning frameworks (e.g., PyTorch, JAX, TensorFlow).
- Experience working with robotic systems such as manipulators, mobile robots, autonomous vehicles, or similar platforms.
- Experience using machine learning in cloud environments (such as Google Cloud and AWS) and edge hardware for real-time deployment and scalability.
- Experience with modern scientific deep learning methods (e.g., Neural ODEs, PINNs, Operator networks, Hamiltonian and Lagrangian neural networks, graph neural networks).
- The ability to develop and evaluate integrated systems.
- Demonstrated leadership in delivering complex, end-to-end robotics solutions with successful Sim2Real transfer for various tasks and automated workflows.
- Prior experience mentoring early career staff, guiding multidisciplinary teams, and shaping research vision and technical roadmaps.
- Proven track record of impactful results, evidenced by successful projects, fellowships, grants, patents, and publications in top robotics and AI conferences/journals (e.g., ICRA, RSS, IROS, CoRL, ACC, CDC, NeurIPS, ICML, CVPR).
- Ability to architect and evaluate integrated robotic systems across simulation and real-world environments.
About the company
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, and flexible work schedules. 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 and Equal Employment Opportunity:
Our laboratory is committed to fostering a work environment where all individuals are treated with fairness and respect while solving critical challenges in fundamental sciences, national security, and energy resiliency. We are an Equal Employment Opportunity employer.
Pacific Northwest National Laboratory (PNNL) is an Equal Opportunity Employer. PNNL considers all applicants for employment without regard to race, religion, color, sex, 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 protected].
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.
HSPD-12 PIV Credential Requirement:
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.