2026 PhD Graduate - Data Scientist / Computer Scientist - Decision Systems

Johns Hopkins Applied Physics Laboratory•Laurel, MD

140d

About The Position

Are you looking for an engaging and impactful career building on the foundations of your academic work? Do you want to build data-driven solutions that offer the explainability vital to decision making? Would you like to be a part of an engaging interdisciplinary intellectual community? If so, consider joining us in the Decision Systems Group (QAX) as we work to enhance the safety and security of the nation through "Critical Contributions to Critical Challenges". We are advancing analytic methods and developing integrated software systems empowering informed decision making. We are working to advance the forefront of national and health security. As a member of our QAX team, you may... Design and develop high-performance, scalable, and resilient decision support systems. Collaborate with internal and external partners to understand and translate system concepts into plans of action. Develop proof of concept prototypes to explore new technologies in the context of our sponsor's missions. Engage in research and analysis to move our approaches from a reactive to a proactive posture.

Requirements

Possess a terminal degree (e.g., PhD, DEng) in Computer Science, Mathematics, Physics, Electrical Engineering, or a similar field
Are proficient in at least one programming language commonly used in data science and/or full-stack development (e.g., Python, Java, JavaScript)
Possess outstanding written and oral communication skills, organizational skills, and a penchant for relationship building
Are able to obtain an Interim Secret clearance to start and a final Secret level security 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.

Nice To Haves

Have prior experience as a researcher or practitioner in any of the following areas: Generative AI, Deep Learning, Optimization, Natural Language Processing, Operations Research, Supply Chain Analysis, Software Engineering, Data Visualization, Data Engineering, DevOps / MLOps, Public Health Surveillance, or Health Informatics.
Have a record of communicating analyses of real-world data sets to audiences with broadly varying technical backgrounds.

Responsibilities

Design and develop high-performance, scalable, and resilient decision support systems.
Collaborate with internal and external partners to understand and translate system concepts into plans of action.
Develop proof of concept prototypes to explore new technologies in the context of our sponsor's missions.
Engage in research and analysis to move our approaches from a reactive to a proactive posture.