Subject Matter Expert IV

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.

KEY 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

EDUCATION & EXPEREINCE: (or equivalent)

• PhD in Engineering or Applied Sciences.
• 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

KNOWLEDGE & SKILLS:

• 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.

TRAVEL : 10% May travel to support semi-annual or annual reviews.

SECURITY CLEARANCE: Active Secret required