2026 PhD Graduate - Machine Learning and Artificial Intelligence

The Johns Hopkins University Applied Physics Laboratory; Laurel (MD); Hybrid; USD 105,000 - 245,000; Full time

Job summary

The Johns Hopkins University Applied Physics Laboratory (APL) is seeking a PhD graduate with expertise in machine learning to support multi-disciplinary teams tackling quantitative tasks for defense and national security applications.

You will join engineers, scientists, statisticians and analysts committed to advancing performance evaluation of national weapons systems. APL emphasizes innovation, integrity, trust, and teamwork.

Qualifications

• Earned PhD in a relevant field and demonstrate strong mathematical foundations for ML.
• Experience with ML libraries (PyTorch, TensorFlow) and adapting methods.
• Proven ability to select appropriate modeling approaches for supervised/unsupervised/reinforcement learning.

Responsibilities

• Work with multi-disciplinary teams to support data collection, processing and analysis for defense-related systems.
• Contribute to full R&D lifecycle including model/algorithm selection, experimentation, analysis and presentation of results.
• Apply statistical and ML expertise to select modeling approaches for complex real-world data.
• Leverage internal funding to shape future research directions.
• Communicate technical knowledge through papers and presentations to technical staff, management and government decision makers.

Skills

Interpersonal skills

ML foundations (probability, stats, LA

ML libraries (PyTorch/TensorFlow)

Modeling techniques—supervised/unsuper

Security clearance eligibility

Education

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

Job description

Description

Do you enjoy exploring and analyzing data to find data-driven solution to complex problems?

Do you want to contribute to work that is crucial to maintaining our national security and strength?

Are you continuously searching for new ways to grow your knowledge and improve your skills?

If you are graduating with a PhD in Statistics, Physics, Mathematics, Computer Science, or a related field, we would love to have you join our team! We are seeking a new PhD graduate with expertise in machine learning to support multi-disciplinary teams performing a variety of quantitative tasks for defense and national security applications. You will be joining a varied team of engineers, software developers, statisticians, data scientists, and analysts who are committed to advancing the state-of-the-art in performance evaluation of the nation's strategic weapons systems throughout their lifecycle. We believe in continually growing our capabilities and cultivating a work environment that embraces innovation, integrity, trust, and teamwork.

As a member of our team, you will…

• 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.

Qualifications

You meet our minimum qualifications for the job if you…

• 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.

You will go above and beyond our minimum requirements if you…

• Have experience in project management or leading technical teams.
• Have experience in writing technical proposals, particularly for government research projects.
• Have experience mentoring students, teaching, or communicating complex technical concepts in academic, research, or professional settings.
• Have 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.
• Have contributed to peer‑reviewed publications, technical reports, or presentations in statistics, machine learning, applied mathematics, or related fields.
• Have experience understanding, developing, or adapting modern AI models and workflows, including large language models, for quantitative analysis and decision support.

About Us

Why Work at APL?

The Johns Hopkins University Applied Physics Laboratory (APL) brings world‑class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.

At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore‑Washington metro area. Learn more about our career opportunities at https://www.jhuapl.edu/careers.

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, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact [e-mail].

The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign‑on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short‑term disability, long‑term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.

Minimum Rate

$105,000 Annually

Maximum Rate

$245,000 Annually