Acoustic Signal Processing Machine Learning Postdoc

Los Alamos National Security LLC; Los Alamos (NM); On-site; USD 60,000 - 80,000; Full time

Benefits offered by this job

Relocation assistance

Tuition assistance

Onsite gym access

Paid time off

Job summary

Los Alamos National Laboratory (LANL) seeks a postdoctoral researcher to advance noninvasive acoustic/ultrasonic characterization with strong AI/ML and signal processing skills. You will automate real-world measurements, develop ML algorithms, and contribute to experimental technique development in complex noisy systems.

The role emphasizes applied research in materials, acoustical imaging, and defect detection, with opportunities to publish, patent, and present; DOE Q clearance is required;

Qualifications

• Ph.D. in Applied Physics, Engineering, Computer Science or closely related field.
• Strong background in signal processing, data analysis, statistics, and ML.
• Proficiency in Matlab, Python, or C++.
• Experience with PyTorch and Scikit-learn.
• Experience applying ML methods to real-world, noisy data.
• Ability to publish research and obtain DOE Q clearance.

Responsibilities

• Develop noninvasive acoustic/ultrasonic characterization methods.
• Automate recording, conditioning, and processing of measurements.
• Create ML algorithms to extract information from signals.
• Contribute to experimental technique development and publications.

Skills

Signal processing

Machine learning

Python

Matlab

C++

PyTorch

Scikit-learn

DL architectures

Education

Ph.D. in Applied Physics, Engineering, Computer Science

Tools

Python

Matlab

C++

PyTorch

Scikit-learn

Job description

What You Will Do

Los 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 postdoctoral researcher 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.

The ideal candidate will be one that has strong AI/ML skills while still having experience in experimental science. Candidates with pure ML or computational science background are less ideal as the work will be highly applied and require the candidate to have a detailed understanding of the physics involved in the work.

What You Need

Minimum Job Requirements:

• 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 computer programming languages like Matlab, Python, or C++
• Experience with standard machine learning software packages like Pytorch, Scikit-learn
• Experience with common deep learning model architectures like MLPs, CNNs, and attention
• Experience 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 record
• Ability to obtain DOE Q clearance (usually requires US citizenship)

Desired Qualifications:

• Knowledge of electronics and typical laboratory test instruments, such as function generators, oscilloscopes and piezoelectric transducers
• Experience with generative learning models like GAN, CVAE, etc.
• Experience working with edge learning on, e.g. FPGA
• Ability to adapt to new requirements for projects and be flexible to learn new areas of research as needed

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.

Contact: Dr. John Greenhall, [e-mail]

Note to Applicants:

Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People's Republic of China-including the special administrative regions of Hong Kong and Macau-as well as citizens of the Islamic Republic of Iran, the Democratic People's Republic of Korea (North Korea), and the Russian Federation, who are not Lawful Permanent Residents ("green card" holders) are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory.

Where You Will Work

Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:

• PPO or High Deductible medical insurance with the same large nationwide network
• Dental and vision insurance
• Free basic life and disability insurance
• Paid childbirth and parental leave
• Award-winning 401(k) (6% matching plus 3.5% annually)
• Learning opportunities and tuition assistance
• Flexible schedules and time off (PTO and holidays)
• Onsite gyms and wellness programs
• Extensive relocation packages (outside a 50 mile radius)

Additional Details

Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.

Clearance: Q

Position will be cleared to this level. Selected applicants will be subject to a background investigation conducted by or on behalf of the Federal Government, and must meet eligibility requirements* for access to classified matter. This position requires a Q clearance, and obtaining such clearance requires US Citizenship except in extremely rare circumstances. Dependent upon the position, additional authorization to access classified information may be required, which may or may not be available to dual citizens. Receipt of a Q clearance and additional access authorization ultimately is a decision of the Federal Government and not of Triad.

*Eligibility requirements: To obtain a clearance, an individual must be at least 18 years of age; U.S. citizenship is required except in very limited circumstances. See DOE Order 472.2 for additional information.

New-Employment Drug Test:

The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.

Internal Applicants:

Regular appointment employees who have served the required period of continuous service in their current position are eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the required period of continuous service, they may only apply for Laboratory jobs with the documented approval of their Division Leader. Please refer to Policy Policy P701 for applicant eligibility requirements.

Equal Opportunity:

Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal, state, and local laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to [e-mail] or call (505)-664-6947.