PhD ML & AI Scientist for National Security

Johns Hopkins Applied Physics Laboratory; Laurel (MD); On-site; USD 105,000 - 245,000; Full time

Job summary

Johns Hopkins Applied Physics Laboratory (APL) invites PhD graduates in data science, statistics, physics, mathematics, or computer science to join a multidisciplinary team. You will apply machine learning to defense and national security problems, collaborating with engineers, statisticians, and analysts to advance performance evaluation of systems.

We value independent initiative, strong communication, and ability to work across domains.

Qualifications

• Have a PhD in Data Science, Statistics, Physics, Mathematics, Computer Science or a related field.
• Demonstrate strong interpersonal skills and the ability to work independently and on a team.
• Have a solid understanding of the mathematical foundations of ML, including probability, statistics, and linear algebra.
• Have experience using modern AI/ML libraries or frameworks (e.g., PyTorch, TensorFlow, or similar), with including adapting or extending methods for domain-specific problems.
• Demonstrate 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.
• Are able to obtain Interim Secret level security clearance by your start date and can ultimately obtain Top Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

Responsibilities

• Work with multi-disciplinary teams to support development of data collection, processing, and analysis efforts to assess the performance of a number of systems supporting the Navy and Air Force.
• Contribute to the full research and development lifecycle for emerging problems. This includes 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.

Skills

ML foundations

PyTorch

TensorFlow

Probability & Statistics

Communication

Education

PhD in Data Science, Statistics, Physics, Mathematics, Computer Science or related field

Tools

Python

SciPy

Job description

Johns Hopkins Applied Physics Laboratory (APL) invites PhD graduates in data science, statistics, physics, mathematics, or computer science to join a multidisciplinary team. You will apply machine learning to defense and national security problems, collaborating with engineers, statisticians, and analysts to advance performance evaluation of systems.

We value independent initiative, strong communication, and ability to work across domains.