Job Description:
Analytical Mechanics Associates, Inc. is seeking a High-Enthalpy Diagnostics Engineer to support the Thermal Protection Materials branch (Code TSM) within the Entry Systems and Technology Division at NASA Ames Research Center. The selected candidate will support ARCTRON (a multi-gas, multi-heat source, plasma chamber for high-temperature catalycity measurements, model validation and thermal protection system (TPS) material down-selection), and related experimental capabilities through development and application of advanced diagnostics, facility characterization, material characterization, and quantitative data analysis for TPS research. This is a full-time, onsite role at Moffett Field, CA. The salary range is $135k-$160k, depending on experience.
Responsibilities- Plan and execute experimental campaigns in ARCTRON and other high-enthalpy, plasma, arc-jet, or related test environments.
- Develop, integrate, calibrate, and operate optical and in-situ plasma diagnostics, including optical emission spectroscopy, absorption spectroscopy, laser-induced fluorescence, imaging, and related techniques.
- Characterize ARCTRON operating conditions and diagnostic performance across priority test regimes.
- Develop measurement models and uncertainty-quantification methods for experimental diagnostics, including uncertainty propagation, thermal modeling, state estimation, and data-assimilation approaches.
- Conduct quantitative analysis of facility, diagnostic, and material-response measurements; compare experimental results with thermal, fluid, plasma, and other numerical models.
- Support TPS material characterization using division equipment, including CT scanning, tomography analysis, image processing, and ARCTRON testing.
- Prototype spatially resolved oxygen and argon temperature measurements using absorption spectroscopy and laser-induced fluorescence.
- Document test procedures, facility conditions, diagnostic configurations, calibrations, assumptions, uncertainties, and test results.
- Coordinate experimental activities with facility personnel, technicians, researchers, computational modelers, and collaborators.
Minimum Qualifications- Master’s degree or higher in Aerospace, Aeronautical or Mechanical Engineering, or a closely related engineering field.
- Background in experimental aerothermodynamics, plasma physics, high-enthalpy testing, combustion, spectroscopy, optical diagnostics, or a related experimental research field.
- Experience planning, conducting, analyzing, and documenting experimental test campaigns.
- Experience with quantitative data analysis, scientific programming, or scripting for engineering analysis and data processing, such as Python, MATLAB, or comparable tools.
- Experience developing, applying, or interpreting diagnostics in high-temperature, plasma, flow, or other demanding experimental environments.
- Ability to document technical work and communicate experimental results clearly. Track record of publication of research findings in reputed international conferences and journals.
- Ability to collaborate across experimental, computational, diagnostic, and multidisciplinary research teams.
- Ability to work full-time on-site at NASA Ames Research Center and travel occasionally, as required.
- This position is open to US Citizens, Legal Permanent Residents and Foreign Nationals except those from countries on NASA’s designated country list.
Preferred Qualifications- Experience with arc-jet, radio-frequency plasma, laser-heating, hypersonic, or other aerospace thermal-test facilities; experience with ARCTRON or similar plasma test platforms is highly desirable.
- Experience with laser absorption spectroscopy, laser-induced fluorescence, Raman spectroscopy, optical emission spectroscopy, spectroradiometry, high-speed imaging, or related diagnostic techniques.
- Experience measuring or inferring gas or plasma temperature, species concentration, enthalpy, heat flux, pressure, or radiative heating.
- Experience with uncertainty quantification, state estimation, Kalman filtering, Bayesian inference, data assimilation, inverse methods, or parameter estimation for experimental measurements.
- Experience analyzing experimental datasets using image processing, signal processing, tomography, visualization, and comparison with numerical predictions.
