Research Scientist

UNC-Chapel Hill • Chapel Hill, NC

4d

About The Position

The position focuses on developing and applying advanced machine learning techniques to improve full-waveform inversion ( FWI ) across a range of imaging domains, including geophysics and medical ultrasound. The successful candidate will be responsible for designing data-driven models that enhance the accuracy, robustness, and computational efficiency of FWI workflows. Key duties include integrating deep learning with physics-based modeling, implementing scalable training strategies, and validating methods on both simulated and experimental datasets. The role also involves close collaboration with domain experts in imaging sciences and high-performance computing to advance next-generation inversion methodologies. Additional responsibilities include publishing research findings in top-tier journals and conferences.

Nice To Haves

• Ph.D. in data and information science, applied mathematics, computer science, geophysics, biomedical engineering, or a related field
• Expertise in inverse problems, machine learning, and wave physics simulations
• Experience with numerical methods and solving PDEs
• Familiarity with full-waveform inversion and high-performance computing
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow)
• Strong publication record and ability to conduct independent research
• Effective communication and collaboration skills across disciplines

Responsibilities

• Designing data-driven models that enhance the accuracy, robustness, and computational efficiency of FWI workflows
• Integrating deep learning with physics-based modeling
• Implementing scalable training strategies
• Validating methods on both simulated and experimental datasets
• Collaborating with domain experts in imaging sciences and high-performance computing to advance next-generation inversion methodologies
• Publishing research findings in top-tier journals and conferences

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree