2026 PhD Graduate - Algorithm Researcher - Artificial Intelligence, Machine Learning, and Information Fusion
Johns Hopkins APL · Laurel, MD · Artificial Intelligence
About this role
Johns Hopkins APL is hiring a junior-level Research Scientist in the machine learning function based in Laurel, MD. The posting calls out experience with Python, TensorFlow, PyTorch, scikit-learn and roughly 2+ years of relevant work. Listed education preference: a Ph.D. or equivalent.
- Role
- Research Scientist
- Function
- machine learning
- Level
- junior
- Track
- Individual contributor
- Location
- Laurel, MD
- Experience
- 2+ years
- Education
- Ph.D. preferred
- Visa
- Not sponsored
- Department
- Artificial Intelligence
- Posted
- Sep 4, 2025
More roles at Johns Hopkins APL
Job description
from Johns Hopkins APL careersDo you have experience developing AI/ML algorithms OR a graduate-level research background in data fusion and/or distributed control?
Do you thrive in a research environment, working alongside an energetic team of scientists and engineers?
Are you ready to help the US secure and maintain leadership in the development and fielding of algorithms for defense systems?
If you are graduating with a PhD degree in Computer Science, Engineering, Mathematics, Statistics, Physics or a related field, we are looking for someone like you to join our team at APL!
We are seeking a highly motivated researcher who will contribute to all phases of the development process. You will be joining a team of engineers and scientists who are at the forefront of APL's mission to provide innovative solutions to critical challenges. Accurate, timely, and actionable information derived from a variety of sources provides the warfighter advantages over its adversaries. Our group at APL identifies, develops, and applies efficient and effective algorithms to support critical capabilities for a variety of DoD missions.
Duties
As a member of the Information Fusion and Artificial Intelligence group you will …
- Research, implement, prototype, and analyze algorithms, quantify and document the performance capabilities and limitations of algorithms for specific tasks, and provide metrics of robustness and confidence in specific approaches.