Location: Los Alamos, NM
Cap-Exempt H-1B Position — No lottery required
**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 graduate student with strong experimental and data analysis skills. We are seeking a highly motivated individual to join a multidisciplinary research team and contribute to the development of an acoustics-based sensor for enhanced geothermal systems. This work involves complex experimental work, as well as significant data analysis and signal processing.** 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 materials and acoustically engineered materials. The work involves the development of new techniques, customized instrumentation and validation of measurements in the field. 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 Need** Minimum Job Requirements: - B.S in Applied Physics, Engineering, Materials Science or a closely related field, earned within the last five years or soon to be completed - Currently enrolled in a graduate program in Applied Physics, Engineering, Materials Science, Geosciences, or a closely related field - Strong technical background in one or more of the following areas: signal processing, advanced data analysis, finite element analysis (especially COMSOL), ultrasonic techniques, nondestructive testing, machine learning, enhanced geothermal systems - Fluency in one or more computer programming languages (e.g., Matlab, Python, Visual Basic, C++, LabVIEW, etc.) - Hands-on experience designing and conducting experiments - Demonstrated expe