Join us and make YOUR mark on the World!
Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.
We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory’s mission.
We have an opening for Postdoctoral Researchers to join our interdisciplinary team of Applied Machine Learning Researchers supporting a variety of application areas including Cyber Security, Climate Modeling, Energy Systems, Bioscience and Advanced Manufacturing. Qualified candidates should have a background in a scientific discipline providing underlying skills in data analytic techniques and a working knowledge of standard machine learning toolkits. While supporting applied research projects, selected candidates will be provided mentorship, practical training, and skill development to develop depth and breadth in machine learning techniques as well as gain exposure to a variety of application areas. These positions are in the Computational Engineering Division (CED) within the Engineering Directorate.
In this role you will
Conduct research into state-of-the-art Machine Learning algorithms relevant to the problem being addressed.
Implement, train and validate proposed algorithms for specific problem domains.
Contribute to the integration of algorithms within larger programmatic systems that require these capabilities.
Collaborate with others in a multidisciplinary team environment to accomplish research goals.
Pursue independent, but complementary, research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings.
Travel as required to coordinate research with collaborators and visit field sites.
Perform other duties as assigned.
Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.
Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods.
Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe.
Demonstrated ability to undertake original research and communicate findings in peer-reviewed publications.
Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.
All your information will be kept confidential according to EEO guidelines.
This is a Postdoctoral appointment with the possibility of extension to a maximum of three years. Eligible candidates are those who have been awarded a PhD at time of hire date.
Why Lawrence Livermore National Laboratory?
Learn more about our company, selection process, position types and security clearances by visiting our Career site.
COVID-19 Vaccination Mandate
LLNL demonstrates its commitment to public safety by requiring that all new Laboratory employees be immunized against COVID-19 unless granted an accommodation under applicable state or federal law. This requirement will apply to all new hires including those who will be working on site, as well as those who will be teleworking.
This position requires a Department of Energy (DOE) Q-level clearance. If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship. For additional information, please see DOE Order 472.2.
Pre-Employment Drug Test
External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Equal Employment Opportunity
LLNL is an affirmative action and equal opportunity employer that values and hires a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.
If you need assistance and/or a reasonable accommodation during the application or the recruiting process, please submit a request via our online form.
California Privacy Notice
The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.
Backup child care
Since its origins, Lawrence Livermore National Laboratory (LLNL) has pushed the limits of science, technology, and research in an effort to better understand the world and protect the people in it—but we do so much more than that. To this day, we continue to innovate, collaborate, and explore, backed by the minds of thousands of talented researchers, operations staff, ...