Science and Technology on a Mission!
For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place.
You will contribute to various efforts in distributed signal processing, distributed machine learning and active sensing at LLNL, in applications including large collaborative autonomous sensor networks and modeling of multimodal electronic health records. In particular, you’ll address cases in which datasets are too large to be communicated to a central processing node and/or cannot be stored or processed on a single node. You will assist in efficient learning and inference techniques for such distributed datasets under communication and delay constraints. You will study both the homogenous case where the data are of the same type and the heterogeneous case where the data are from different types of sensors. This position will be in Computational Engineering Division within the Engineering Directorate.
- Collaborate with Laboratory researchers on applications of decentralized inference and learning techniques.
- Work on theoretical performance guarantees of developed algorithms.
- Contribute to distributed signal processing algorithm development and scalability problems in collaborative sensor networks and medical applications of machine learning.
- Perform other duties as assigned.
- Must be a continuing faculty or teacher affiliated at an accredited institution.
- Experience in decentralized signal processing and decentralized learning/inference methods
- A significant publication record in theory and algorithms related to decentralized inference and machine learning.
- PhD in Electrical Engineering
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.
Security Clearance: None required.
Note: This is a Temporary Faculty Scholar appointment with the possibility of extension.
Lawrence Livermore National Laboratory (LLNL), located in the San Francisco Bay Area (East Bay), is a premier applied science laboratory that is part of the National Nuclear Security Administration (NNSA) within the Department of Energy (DOE). LLNL's mission is strengthening national security by developing and applying cutting-edge science, technology, and engineering that respond with vision, quality, integrity, and technical excellence to scientific issues of national importance. The Laboratory has a current annual budget of about $1.8 billion, employing approximately 6,500 employees.
LLNL is an affirmative action/ equal opportunity employer. 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, protected veteran status, age, citizenship, or any other characteristic protected by law.
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