Acoustic Signal Processing Machine Learning Postdoc

Overview

Acoustic Signal Processing Machine Learning Postdoc at Los Alamos National Laboratory (LANL). The Applied Acoustics Team (MPA-11) seeks a postdoctoral researcher with strong computational skills and a solid background in signal processing and machine learning to contribute to noninvasive acoustic/ultrasonic characterization and monitoring in complex, noisy systems.

Automate the recording, conditioning, and processing of real-world measurements in the time- and frequency-domain, and develop machine learning algorithms to extract useful information from signals. Participate in experimental acoustic measurement technique development and contribute to the development of a new sensing technologies. Collaborate with a multidisciplinary team, publish results, and present work to sponsors and conferences. Work includes development of new techniques, customized instrumentation, and analysis algorithms;

contribute to patents and publications.

• Ph.D. in Applied Physics, Engineering, Computer Science, or a closely related field, earned within the last five years or soon to be completed
• Strong technical background in one or more of the following areas: signal processing, advanced data analysis, statistics, ultrasonic techniques, nondestructive testing, and machine learning
• Fluency in one or more programming languages such as Matlab, Python, or C++
• Experience with standard machine learning software packages like PyTorch and Scikit-learn
• Experience with common deep learning model architectures such as MLPs, CNNs, and transformers
• Experience developing, implementing, and testing machine learning methods for signal-processing applications using complex, noisy real-world data
• Demonstrated ability to conduct original scientific research through peer-reviewed publication or conference record

• Knowledge of electronics and typical laboratory test instruments (e.g., function generators, oscilloscopes, piezoelectric transducers)
• Experience with generative learning models (e.g., GANs, CVAEs)
• Experience with edge learning on platforms such as FPGA
• Ability to adapt to new project requirements and learn new areas of research as needed
• Ability to obtain DOE Q clearance (usually requires US citizenship)

The work location for this position is onsite in Los Alamos, NM. All work locations are at management discretion.

Due to federal restrictions, certain foreign nationals may be prohibited from accessing facilities supporting national security laboratories and related activities.

LANL offers a comprehensive benefits package, including medical insurance, dental and vision coverage, life and disability insurance, parental leave, 401(k) with employer match, tuition assistance, flexible schedules and PTO, onsite gyms and wellness programs, and relocation support for eligible candidates.

Employment with Triad requires favorable decision by NNSA indicating suitability under NNSA Supplemental Directive 206.2 (U.S. citizens). Foreign nationals are subject to DOE orders and similar requirements. New-employment drug testing applies; marijuana use remains illegal under federal law. Equal Opportunity: LANL is an equal opportunity employer and provides accommodations for applicants with disabilities upon request.