Acoustic Signal Processing Machine Learning Graduate ...

What You Will DoLos Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in science and engineering on behalf of national security. The Applied Acoustics Team (MPA-11) is looking for a Graduate student with strong computational skills and solid background in signal processing and machine learning. We are seeking a highly motivated individual to join a multidisciplinary research team and contribute to the development of a new noninvasive acoustic/ultrasonic characterization and monitoring in complex, noisy systems. This work involves automating the recording, conditioning, and processing of real-world measurements in the time- and frequency-domain; and then developing machine learning algorithms to extract useful information from the signals. The work will also involve some experimental acoustic measurement technique development.Our current work focuses on applied research for material characterization (solids, liquids, gases), acoustical imaging, nonlinear acoustics, acoustic separation of two-phase systems, detection of corrosion and other defects in structures and monitoring the change in structures over time. The work involves development of new techniques, customized instrumentation, and analysis algorithms. The successful candidate will be expected to contribute to the development of new sensing technologies, patents and publications. There will be opportunities to work in a wide range of areas, to innovate, and present work to sponsors and conferences.What You NeedMinimum Job Requirements:Graduate Student in Applied Physics, Engineering, Computer Science, or a closely related field, earned within the last five years or soon to be completedStrong technical background in one or more of the following areas: signal processing, advanced data analysis, statistics, ultrasonic techniques, nondestructive testing, and machine learningFluency in one or more computer programming languages like Matlab, Python, or C++Experience with standard machine learning software packages like Pytorch, Scikit-learnExperience with common deep learning model architectures like MLPs, CNNs, and transformersExperience developing, implementing, and testing machine learning methods for signal-processing applications using complex, noisy real-world data.Demonstrated experience in conducting original scientific research through peer-reviewed publication or conference recordDesired Qualifications:Knowledge of electronics and typical laboratory test instruments, such as function generators, oscilloscopes and piezoelectric transducersExperience with generative learning models like GAN, CVAE, etc.Experience working with edge learning on, e.g. FPGAAbility to adapt to new requirements for projects and be flexible to learn new areas of research as neededAbility to obtain DOE Q clearance (usually requires US citizenship)Work Environment:Work Location: The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.

Created: 2025-11-07