PhD Intern

We are seeking a highly motivated engineer with strong expertise in signal processing, ultrasound/wave propagation, and wave–material interaction to develop and deploy advanced data analysis solutions for complex experimental datasets. The ideal candidate combines deep theoretical knowledge with hands-on experimental skills to translate physics-based insights into robust algorithms and tools.

Site Overview

Established in 2000, the John F. Welch Technology Center (JFWTC) in Bengaluru is our multidisciplinary research and engineering center. Engineers and scientists at JFWTC have contributed to hundreds of aviation patents, pioneering breakthroughs in engine technologies, advanced materials, and additive manufacturing.

Essential Responsibilities

• Design and develop signal processing algorithms for ultrasound and guided-wave applications, including filtering, deconvolution, time–frequency analysis, beamforming, and dispersion compensation.
• Model wave propagation and wave–material interactions in metals, composites, and advanced materials; incorporate scattering, attenuation, mode conversion, and anisotropy into analysis workflows.
• Build advanced data analysis pipelines using statistical methods and machine learning for feature extraction, anomaly detection, classification, and uncertainty quantification; deliver production-quality code and documentation.
• Plan and execute experiments, including sensor/fixture selection, calibration, data acquisition, and validation; develop test plans, safety protocols, and repeatable measurement procedures.
• Analyze large experimental datasets, perform data cleaning, signal conditioning, and parameter estimation; generate clear visualizations and technical reports with quantitative conclusions.

Ideal Candidate:

Should have experience in signal processing: sampling theory, spectral analysis, digital filtering, time–frequency methods, beamforming, array processing.

Required Qualifications

• MS or PhD in Electrical Engineering, Mechanical Engineering, Applied Physics, Acoustics, Materials Science, or related field.
• Strong foundation in signal processing: sampling theory, spectral analysis, digital filtering, time–frequency methods, beamforming, array processing.
• Demonstrated expertise in ultrasound/wave propagation and wave–material interaction (e.g., dispersion, attenuation, nonlinearity, anisotropy, scattering).
• Proficiency in advanced data analysis techniques: statistical inference, optimization, regression/classification, anomaly detection, uncertainty quantification; experience with Python or MATLAB.

Preferred Qualifications

• Experience with modeling and simulation: COMSOL, Abaqus, LS-DYNA, PZFlex, k-Wave, OnScale, or custom FDTD/FEM solvers.
• Knowledge of materials behavior (metals, composites, ceramics), microstructure effects on acoustic properties, and temperature/pressure/operational effects.
• Humble: respectful, receptive, agile, eager to learn
  
• Transparent: shares critical information, speaks with candor, contributes constructively
  
• Focused: quick learner, strategically prioritizes work, committed
  
• Leadership ability: strong communicator, decision-maker, collaborative
  
• Problem solver: analytical-minded, challenges existing processes, critical thinker.
  

At GE Aerospace, we have a relentless dedication to the future of safe and more sustainable flight and believe in our talented people to make it happen. Here, you will have the opportunity to work on really cool things with really smart and collaborative people. Together, we will mobilize a new era of growth in aerospace and defense. Where others stop, we accelerate.

Relocation Assistance Provided: Yes