Fiber Optic Sensing Post-Master's Student

** What You Will Do*
* The Earth and Environmental Sciences Division (EES-17) at Los Alamos National Laboratory is seeking a highly motivated Post-Master's Student to join a multidisciplinary research team developing advanced sensing and signal processing techniques for geophysical and national security applications.

The successful candidate will contribute to research focused on characterizing energetic phenomena using advanced sensor technologies, including fiber optic sensing. Research activities span laboratory experiments, field deployments, and computational analysis, providing opportunities to work on projects ranging from experimental design and data collection to algorithm development and scientific interpretation.

The selected candidate will work closely with scientists and engineers to develop software for processing large scientific datasets, apply digital signal processing and machine learning techniques to detect and characterize signals, and participate in laboratory and field experiments. This position offers the opportunity to contribute to cutting-edge research while gaining hands-on experience with advanced sensing technologies and real-world data acquisition.

+ Develop Python software to process, visualize, and analyze large scientific dataset from energetic experiments and geophysical monitoring campaigns.

+  Apply digital signal processing, statistical methods, and machine learning techniques to detect, locate, and characterize signals.

+  Develop and evaluate algorithms for scientific data analysis and event detection.

+  Assist with laboratory experiments and field deployments, including sensor installation, data acquisition, and experimental setup.

+  Collaborate with scientists and engineers from multiple disciplines to solve challenging sensing problems.

+  Present research results through technical reports, presentations, and scientific publications.

** What You Need*
* ** Minimum

Job Requirements:

*
* ** Education/Experience** :
Recently completed a Master's degree in Physics, Electrical Engineering, Computer Science, Geophysics, Applied Mathematics, Engineering, or a related STEM discipline.

** Desired

Qualifications:

*
* +

Experience with experimental measurements or field data collection.

+  Strong programming experience with scientific Python (preferred) or in Matlab.

+  Coursework or experience in digital signal processing, time series analysis, machine learning, or scientific computing.

+  

Experience with Linux and Git.

+  Experience or coursework in optics, sensor systems, or geophysics.

+  Demonstrated analytical and problem-solving skills.

+  Excellent written and verbal communication skills and the ability to work effectively on a collaborative research team.

+  Ability to obtain a Q clearance, which requires U.S. citizenship.

*
* 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.

** 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.

Anticipated travel to field sites at Los Alamos National Laboratory and within the United States.

Interested candidates should submit the following application materials:

+ A current resumé or curriculum vitae (CV)

+  An unofficial transcript

+  A brief statement of interest (1 page or less) describing your background, research interests, programming experience, and why you are interested in this position

+  Contact information for two to three professional or academic references

+  Applications will be accepted through December 31, 2026. Review of applications will begin…