PhD Graduate – Artificial Intelligence and Complex Systems Researcher

Overview

2026 PhD Graduate – Artificial Intelligence and Complex Systems Researcher. Join Johns Hopkins Applied Physics Laboratory to apply AI and data-driven methods to unlock insights from complex, high-dimensional data and address real-world challenges in domains such as earth systems, materials science, biology, and advanced manufacturing. We seek creative problem solvers with initiative to contribute to AI projects for complex systems within the Complex Systems Group, part of the Intelligent Systems Center.

• Design, train, and develop machine learning (ML) algorithms for complex systems.
• Collect and prepare data, evaluate models, and program in relevant languages.
• Establish collaborations with domain experts and seek opportunities for internal or external funding.
• Collaborate with Program Managers to identify opportunities to grow our work in key areas.
• Publish research in impactful venues and engage with external researchers, collaborators, and sponsors.

• Have a PhD in AI, Mathematics, Statistics, Computer Science, Data Science, Engineering, or a related field.
• Have published research in peer‑reviewed journals and/or conferences.
• Experience with AI/ML algorithms, data science, deep learning, graph theory, software development, or statistical analysis.
• Proficiency in Python programming.
• Ability to obtain Interim Secret clearance by start date and ultimately obtain Top Secret clearance; U.S. citizenship required.

• Background in earth systems, materials, chemistry, biology, additive manufacturing, or other complex systems.
• Experience in project management or leading technical teams.
• Experience writing technical proposals for government sponsors.
• Experience applying AI/ML to real-world data (e.g., remote sensing, earth systems, materials, omics, additive manufacturing).
• Proficiency in AI/ML software development and libraries such as PyTorch and Hugging Face.
• Familiarity with advanced AI methods (agentic AI, physics-informed neural networks, neural operators, diffusion modeling, graph neural networks, Bayesian optimization, active learning, LLMs, symbolic AI).

The Johns Hopkins University Applied Physics Laboratory (APL) solves critical defense, security, space and science challenges. We value a welcoming culture, growth, and collaboration with inspiring teammates. APL offers generous benefits, education assistance, retirement contributions, and work–life balance. Our campus is in the Baltimore-Washington metro area. Learn more at http://(Use the "Apply for this Job" box below)..

All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other characteristic protected by law. APL provides reasonable accommodations; contact Accommodations for accommodations in the hiring process.

The posted pay range is a good-faith range at the time of posting and may vary based on location, experience, market conditions, education, and internal parity. Base pay range: $/yr - $/yr. Salary details are discussed with the recruiter.