2026 PhD Graduate - Machine Learning and Artificial Intelligence

Johns Hopkins Applied Physics Laboratory•Laurel, MD

19h•Onsite

About The Position

This role is for a PhD graduate with expertise in machine learning to support multi-disciplinary teams performing quantitative tasks for defense and national security applications. The position involves working with a diverse team of engineers, software developers, statisticians, data scientists, and analysts to advance the state-of-the-art in performance evaluation of strategic weapons systems. The company fosters a culture of innovation, integrity, trust, and teamwork, with a focus on continuous growth and learning.

Requirements

PhD in Data Science, Statistics, Physics, Mathematics, Computer Science or a related field.
Strong interpersonal skills and the ability to work independently and on a team.
Solid understanding of the mathematical foundations of ML, including probability, statistics, and linear algebra.
Experience using modern AI/ML libraries or frameworks (e.g., PyTorch, TensorFlow, or similar), with including adapting or extending methods for domain-specific problems.
Experience selecting appropriate modeling techniques for supervised, unsupervised, or reinforcement learning problems in research or real-world settings, with an understanding of when and why they are appropriate.
Ability to obtain Interim Secret level security clearance by start date and ultimately obtain Top Secret level clearance.
U.S. citizenship.

Nice To Haves

Experience in project management or leading technical teams.
Experience in writing technical proposals, particularly for government research projects.
Experience mentoring students, teaching, or communicating complex technical concepts in academic, research, or professional settings.
Experience applying machine learning methods to scientific, engineering, or data analysis problems, including areas such as computer vision, NLP, time-series analysis, or scientific machine learning.
Contributions to peer-reviewed publications, technical reports, or presentations in statistics, machine learning, applied mathematics, or related fields.
Experience understanding, developing, or adapting modern AI models and workflows, including large language models, for quantitative analysis and decision support.

Responsibilities

Work with multi-disciplinary teams to support development of data collection, processing, and analysis efforts to assess the performance of systems supporting the Navy and Air Force.
Contribute to the full research and development lifecycle for emerging problems, including model and algorithm selection, experimentation, analysis, and presentation of results.
Apply appropriate statistical and machine learning expertise towards selecting modeling approaches for complex, real-world data.
Use internal funding opportunities to shape the direction of future research.
Communicate technical knowledge by articulating ideas clearly through papers and presentations to technical staff, management, and government decision makers.