AI/ML Research Scientist — Physics‑Informed Acoustic Modeling

Peraton; Mississippi; On-site; USD 104,000 - 166,000; Full time

Job summary

Peraton seeks an AI/ML Research Scientist to work onsite at the Stennis Space Center, focusing on underwater acoustics and physics-based ML methods. You will develop surrogate models, physics-informed networks, and generative approaches to accelerate naval-relevant simulations.

You will collaborate with multidisciplinary teams, design controlled experiments, and ensure reproducible research software and documentation.

Qualifications

• 8+ years with BS/BA; 6+ years with MS/MA; 3+ years with PhD.
• Ability to obtain and maintain a Secret security clearance
• U.S. citizenship required
• Strong analytical and quantitative research skills
• Experience applying ML/DL to scientific/engineering problems
• Proficiency with ML frameworks: PyTorch, TensorFlow, or JAX
• Knowledge of neural networks, regularization, generative modeling, reproducible experiments
• Ability to design controlled experiments and communicate results
• Ability to work independently and with multidisciplinary teams

Responsibilities

• Collaborate with acousticians, physicists, engineers, and other experts to improve ML approaches for complex problems
• Conduct research in deep learning, generative AI, LLMs for scientific applications
• Develop physics-informed neural networks, surrogate models, and hybrid physics-ML methods
• Design and run controlled experiments to train and evaluate models
• Assess model accuracy, robustness, and generalization to new conditions
• Create fast ML surrogates to reduce full-physics simulation costs
• Translate physics requirements into ML data representations and metrics
• Maintain reproducible research software and documentation
• Communicate conclusions via reports and briefings

Skills

Machine learning

Deep learning

Scientific computing

Python

Research

Education

PhD

MS/MA

BS/BA

Tools

PyTorch

TensorFlow

JAX

Job description

Peraton seeks an AI/ML Research Scientist to work onsite at the Stennis Space Center, focusing on underwater acoustics and physics-based ML methods. You will develop surrogate models, physics-informed networks, and generative approaches to accelerate naval-relevant simulations.

You will collaborate with multidisciplinary teams, design controlled experiments, and ensure reproducible research software and documentation.