Subject Matter Expert IV

IntrepidGS•Aberdeen Proving Ground, MD

1d•Onsite

About The Position

IAP is seeking a Subject Matter Expert IV to support DEVCOM Army Research Laboratory (ARL) Army Research Directorate in their Applied Research for the Advancement of S&T Priorities (ARAP) - Classical-Quantum Hybrid Constructs to Advance Weapons Science (CLAWS). CLAWS brings disruptive chip-scale quantum photonic devices to the joint fight by combining classical and quantum constructs to revolutionize weapon science, enabling greater precision at longer range for higher lethality. A subject matter expert with Artificial Intelligence (AI) experience is required to develop, benchmark, and validate machine-learning (ML) methods for the prediction, classification, and reconstruction of orbital angular momentum (OAM) states in vortex beams for real-time positioning of the system in motion using interferometric Inertial Measuring Unit (IMU). Location will be at Aberdeen Proving Grounds, Maryland.

Requirements

PhD in Engineering or Applied Sciences. (or equivalent)
10 years’ experience in technology design and development of hardware systems or subsystems.
5 years’ experience designing, developing, and testing in RDT&E directly related to the PWS
Thorough knowledge Microsoft Office Suite.
Attention to detail and ability to handle multiple tasks independently.
Excellent follow-through and time management skills.
Excellent communication and interpersonal skills.
Active Secret required

Responsibilities

Deliver a ML-enabled OAM sensing framework that can infer or recover OAM content from intensity, phase, interferometric, and/or sparse-sensor observations under realistic distortion conditions.
Create a curated simulation-first dataset, with experimental extension, covering single-mode and multiplexed OAM states across controlled disturbance regimes.
Develop baseline classifiers for topological charge identification using full-frame and sparse-point features.
Integrate the best-performing methods into a documented prototype workflow suitable for transition to communications, imaging, or adaptive-optics studies.
Establish the operating concept, measurement assumptions, target OAM ranges, computational environment, and evaluation plan.
Produce a literature-grounded design baseline spanning OAM generation, measurement, communications relevance, and recent ML methods.
Build a reproducible dataset covering Laguerre-Gaussian and related OAM modes, topological charge ranges, modal superpositions, propagation effects, detector noise, and controlled distortions based on laboratory-acquired measurements to enable simulation-to-real validation.
Develop benchmark models for single-mode OAM classification and/or regression of topological charge.
Compare conventional image-based CNN/ResNet baselines with lower-dimensional encodings such as sparse-point or engineered features inspired by the source document.
Integrate data pipeline, trained models, evaluation scripts, and documentation into a demonstration package.
Conduct validation against metrics, and recommend next-phase work for fieldable sensing, communications, imaging, or quantum/measurement applications.
Provide bi-weekly status updates (word doc or PowerPoint)
Participate in meetings with the government
Provide deliverables on-time within government schedule