- Conduct cutting-edge research to develop new AI techniques and algorithms for RF signal processing, including but not limited to automatic modulation recognition, signal detection and classification, and adaptive communication systems.
- Apply machine learning and deep learning methodologies to improve the analysis, interpretation, and management of RF signals in noisy and contested environments.
- Collaborate with cross-disciplinary teams to integrate AI technologies into existing and next-generation RF communication systems, ensuring they meet stringent security and reliability standards.
- Design, implement, and iterate on novel deep learning methods to directly address National Security problems.
- Be able to recreate state of the art architectures, training techniques and digital signal processing blocks from journal publications with minimal examples and/or author code access.
- Stay abreast of advancements in AI, machine learning, and RF technologies to identify opportunities for innovation and improvement in national security applications. Qualifications
- BS/BA and 5+ years of relevant work experience -OR-
- MS/MA and 3+ years of relevant work experience -OR-
- PhD with 1+ year of relevant experience
- Highly experienced in Python development and common associated libraries such as Numpy and Scipy.
- Experience developing, training, and testing machine learning models in frameworks like PyTorch and Sklearn.
- Experience applying machine learning and artificial intelligence to communications, signal processing or time series signals.
- 3+ years of experience with signal processing or electrical engineering sub-domain.
- 3+ years in machine learning or applied science/research in academia or industry.
- 5+ years of experience with general purpose programming language (Python preferred).
- Ability to obtain an TS/SCI clearance Hazardous Working Conditions/Environment
- U.S. Citizenship
- Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
- Drug Testing: All Security Clearance positions are Testing Designated Positions, which means that the candidate selected is subject to pre-employment and random drug testing. In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).
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Senior Data Scientist 3 - Richland, United States - Pacific Northwest National Laboratory
Description
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.
Minimum Qualifications:
Preferred Qualifications:
Not applicable.
Additional InformationThis position requires the ability to obtain and maintain a federal security clearance.
Requirements:
Note: Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy until non-use of illegal drugs, including marijuana, for 12 months can be demonstrated.
Testing Designated PositionThis position is a Testing Designated Position (TDP). The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.
